Upskill with Kanth: Recent Episodes
BEPEC
Hosted by Rajeev Kanth to Build your skills on Data Science, Artificial intelligence, Machine Learning, Deep Learning e.t.c. from our podcasts. Listen to best podcasts like machine learning algorithms, data science projects, data science resume building tips, data science algorithms, data science job life, machine learning applications, machine learning implementations, big data e.t.c. from this top podcasts in the industry. Listen now in iTunes, buzzsprout, Spotify, anchor FM e.t.c. Learn Data Science, Machine learning, AI from Top#1 Data Science and AI Career Transition Program Provider - www.bepec.inWho is Rajeev Kanth:Rajeev Kanth is a Data Scientist and Six Sigma Certified. He is a Data Science Consultant for various Top-MNC's like Nokia, EY, Cognizant, BMW etc. Rajeev Kanth delivered end-to-end AI Solutions using Machine Learning and Deep Learning on Embedded Devices. Built various AI Solutions which impacted financial gains and human effort reduction. Rajeev Kanth is an Orator & Mentor who delivered AI, Machine Learning, Deep Learning, IoT, Industry 4.0 & Digital Twin Customised Training Programs across Dubai, Malaysia, Singapore, South Africa, Sudan etc. Rajeev Kanth delivered more than 100+ training on both sides like client-side and the vendor side.
Ghost jobs are job listings that companies post but have little or no intention of filling. This phenomenon is increasing for several reasons
Website:
https://bepec.in/career-transition-programs/
Youtube:
https://www.youtube.com/@BEPEC
BEPEC Linkedin:
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Mentor Linkedin:
https://www.linkedin.com/in/rajeev-kanth-6222a618a/?originalSubdomain=in
BEPEC Instagram:
https://www.instagram.com/bepec_solutions/
Mentor Kanth Instagram
https://www.instagram.com/meet_kanth/?hl=en
Host : www.instagram.com/meet_kanth/
Whatsapp Us: +919121516181
Welcome to "Statistics for Analysis and Prediction," a podcast that makes data easy to understand and use. Join us as we explore how statistics help us analyze data and predict future trends. Whether you're new to the field or a seasoned expert, you'll find practical tips, real-world examples, and insights from professionals. Tune in to learn how you can harness the power of statistics to make better decisions in your work and everyday life
Website:
https://bepec.in/career-transition-programs/
Youtube:
https://www.youtube.com/@BEPEC
BEPEC Linkedin:
https://www.linkedin.com/company/bepec-solutions/mycompany/
BEPEC Facebook:
https://www.facebook.com/Bepecsolutions/
Mentor Linkedin:
https://www.linkedin.com/in/rajeev-kanth-6222a618a/?originalSubdomain=in
BEPEC Instagram:
https://www.instagram.com/bepec_solutions/
Mentor Kanth Instagram
https://www.instagram.com/meet_kanth/?hl=en
Struggling with Data Analytics, Data Science, AI, Generative AI & Data Engineering Career Transition??
Book 1-on-1 Career Mentorship Call: https://bepec.in/registration-form/
Join 75K+ Youtube Subscriber Family & More Data Analytics, Data Science, AI Content: https://www.youtube.com/@BEPEC/?sub_confirmation=1
Join 170K+ Instagram Family & More Content on AI, DA, DS, ML, Gen AI & Data Engineering: https://www.instagram.com/meet_kanth
Connect with me on LinkedIn: https://www.linkedin.com/in/rajeev-kanth-6222a618a
Crack Data Science Job?? Everyone is discussing online, and many articles, webinars, etc., on that. Listen to this podcast and get clarity on everything related to Data Science and Career Transition.
If you have any queries? Please DM me on Instagram: www.instagram.com/meet_kanth/
If you need detailed Transition Roadmap & Interview Procedure: https://bepec.in/registration-form/
Find our Courses: https://bepec.in/career-transition-programs/
Only one Job-Role Oriented Data Analytics Job Simulation Program to Build Experience in Data Analytics.
No need to invest 1Lakh + Fees on Data Analytics Programs, Join our Job Role Oriented Program and Learn Job Demanded Skills + Build Experience = 100% Career Transition into Data Analytics.
What you will learn:
1. Python Programming
2. R Programming
3. Statistics
4. Power BI
5. Tableau
6. MySql
7. Interview Preparation
8. Mock Interviews
9. Resume Building
10. Linkedin Optimization
11. Job Portal Optimization
12. Projects to place in Resume
Join our new upcoming batch on Job Role Oriented Data Analytics with Power BI and make your transition with Hike.
Join here: https://www.bepec.in/data-analytics-training
Job role oriented Data Science Build Experience Program
No.1 Agenda Job-Ready Agenda on Data Science/Machine Learning with Experience
✅To get a job in Data Science/AI, One must build a portfolio. ✅Learners are wasting time than money due to improper roadmap on Data Science/AI
✅To speak with the mentor on Instagram @meet_kanth✅
🔥
✅The only course which builds real-time experience in Data Science/Machine Learning/AI/Data Analytics🔥
✅Join our BEPEC Data Science/AI/Machine Learning Job Simulation Career Transition Program:
1-on-1 personalised roadmap discussion with the mentor before the program✅
✅
Enrol Our Career Transition Program on Data Science/AI/Machine Learning contains below topics
1. Induction Classes
2. Mastering Python from basics
3. Statistics, ML, NLP & Advanced ML
4. AI/MLOps/Streamlit, Pycaret & Heroku Deployment
5. CMLA for Data Science Lifecycle
6. Tableau
7. Excel
8. Power BI
9. Deep Learning[Feed Forward Neural Networks]
10. Computer Vision using Tensorflow
11. Forecasting
12. Transfer Learning
13. MySQL
14. Paid Internship with BEPEC on Data Science/AI
15. Data Science with R
16. AWS Sagemaker Studio
Join our course: https://www.bepec.in/data-science-career-transition
100% Guarantee Crack any Python Interview
Learn Python Tutorial for Beginners, Check out this #1 Python Lecture on Introduction to Python
Everyone wants to be a Data Scientist/AI/Machine Learning/Data Analyst but are you learning company-demanded skills?
To get a job in Data Science/AI, One must build a portfolio.
✅Learners are wasting time than money due to improper roadmap on Data Science/AI
To speak with the mentor on Instagram @meet_kanth✅🔥
The only course which builds real-time experience in Data Science/Machine Learning/AI/Data Analytics🔥
Join our BEPEC Data Science/AI/Machine Learning Career Transition Program:
1-on-1 personalized roadmap discussion with the mentor before the program✅
✅
Enroll Our Career Transition Program on Data Science/AI/Machine Learning contains below topics
1. Induction Classes
2. Mastering Python from basics
3. Statistics, ML, NLP & Advanced ML
4. AI/MLOps/Streamlit & Heroku Deployment
5. CMLA for Data Science Lifecycle
6. Tableau
7. Excel
8. Power BI
9. Deep Learning[Feed Forward Neural Networks]
10. Computer Vision using Tensorflow
11. Forecasting
12. Transfer Learning
13. MySQL
14. Paid Internship with BEPEC on Data Science/AI
15. Data Science with R
16. AWS Sagemaker Studio
Key Takeaways:
1. Internship while learning the course
2. Paid Internship Opportunity while learning course(You need to crack the interview)
3. Unique Live Projects which increase your resume selection
4. 3+ POC which are mandatory for interviews
5. Customised Career Transition Roadmap based on learners' challenges
6. 100% Support until you get placed
7. Flexible entry & exit points, you can attend training any number of times until you get placed.
8. Mindmap Driven Learning for Revision and Easy Learning while Preparing for Interviews
11. Holistic Learning with 360+ Hours of Content
12. Tuition Classes on Weekdays
13. Weekend Live Classes on Saturday & Sunday
Instagram: https://www.instagram.com/meet_kanth/
Linkedin: https://www.linkedin.com/in/rajeev-kanth-6222a618a/
Spotify: https://open.spotify.com/show/0JDDBdl7aHtoBBwQuCyHV4
Check this out: https://linktr.ee/BepecSolutions
Ways to get a job || 4 Different Types Of Jobs
Everyone wants to be a Data Scientist/AI/Machine Learning/Data Analyst but are you learning company-demanded skills?
To get a job in Data Science/AI, One must build a portfolio.
✅Learners are wasting time than money due to improper roadmap on Data Science/AI
To speak with the mentor on Instagram @meet_kanth✅🔥
The only course which builds real-time experience in Data Science/Machine Learning/AI/Data Analytics🔥
Join our BEPEC Data Science/AI/Machine Learning Career Transition Program:
1-on-1 personalized roadmap discussion with the mentor before the program✅
✅
Enroll Our Career Transition Program on Data Science/AI/Machine Learning contains below topics
1. Induction Classes
2. Mastering Python from basics
3. Statistics, ML, NLP & Advanced ML
4. AI/MLOps/Streamlit & Heroku Deployment
5. CMLA for Data Science Lifecycle
6. Tableau
7. Excel
8. Power BI
9. Deep Learning[Feed Forward Neural Networks]
10. Computer Vision using Tensorflow
11. Forecasting
12. Transfer Learning
13. MySQL
14. Paid Internship with BEPEC on Data Science/AI
15. Data Science with R
16. AWS Sagemaker Studio
Key Takeaways:
1. Internship while learning the course
2. Paid Internship Opportunity while learning course(You need to crack the interview)
3. Unique Live Projects which increase your resume selection
4. 3+ POC which are mandatory for interviews
5. Customised Career Transition Roadmap based on learners' challenges
6. 100% Support until you get placed
7. Flexible entry & exit points, you can attend training any number of times until you get placed.
8. Mindmap Driven Learning for Revision and Easy Learning while Preparing for Interviews
11. Holistic Learning with 360+ Hours of Content
12. Tuition Classes on Weekdays
13. Weekend Live Classes on Saturday & Sunday
Instagram: https://www.instagram.com/meet_kanth/
Linkedin: https://www.linkedin.com/in/rajeev-kanth-6222a618a/
Spotify: https://open.spotify.com/show/0JDDBdl7aHtoBBwQuCyHV4
Check this out: https://linktr.ee/BepecSolutions
Pathways- The Revolutionary AI Model
Everyone wants to be a Data Scientist/AI/Machine Learning/Data Analyst but are you learning company-demanded skills?
To get a job in Data Science/AI, One must build a portfolio.
✅Learners are wasting time than money due to improper roadmap on Data Science/AI
To speak with the mentor on Instagram @meet_kanth✅🔥
The only course which builds real-time experience in Data Science/Machine Learning/AI/Data Analytics🔥
Join our BEPEC Data Science/AI/Machine Learning Career Transition Program:
1-on-1 personalized roadmap discussion with the mentor before the program✅
✅
Enroll Our Career Transition Program on Data Science/AI/Machine Learning contains below topics
1. Induction Classes
2. Mastering Python from basics
3. Statistics, ML, NLP & Advanced ML
4. AI/MLOps/Streamlit & Heroku Deployment
5. CMLA for Data Science Lifecycle
6. Tableau
7. Excel
8. Power BI
9. Deep Learning[Feed Forward Neural Networks]
10. Computer Vision using Tensorflow
11. Forecasting
12. Transfer Learning
13. MySQL
14. Paid Internship with BEPEC on Data Science/AI
15. Data Science with R
16. AWS Sagemaker Studio
Key Takeaways:
1. Internship while learning the course
2. Paid Internship Opportunity while learning course(You need to crack the interview)
3. Unique Live Projects which increase your resume selection
4. 3+ POC which are mandatory for interviews
5. Customised Career Transition Roadmap based on learners' challenges
6. 100% Support until you get placed
7. Flexible entry & exit points, you can attend training any number of times until you get placed.
8. Mindmap Driven Learning for Revision and Easy Learning while Preparing for Interviews
11. Holistic Learning with 360+ Hours of Content
12. Tuition Classes on Weekdays
13. Weekend Live Classes on Saturday & Sunday
Instagram: https://www.instagram.com/meet_kanth/
Linkedin: https://www.linkedin.com/in/rajeev-kanth-6222a618a/
Spotify: https://open.spotify.com/show/0JDDBdl7aHtoBBwQuCyHV4
Check this out: https://linktr.ee/BepecSolutions
Everyone wants to be a Data Scientist/AI/Machine Learning/Data Analyst but are you learning company-demanded skills?
To get a job in Data Science/AI, One must build a portfolio.
✅Learners are wasting time than money due to improper roadmap on Data Science/AI
To speak with the mentor on Instagram @meet_kanth✅🔥
The only course which builds real-time experience in Data Science/Machine Learning/AI/Data Analytics🔥
Join our BEPEC Data Science/AI/Machine Learning Career Transition Program:
1-on-1 personalized roadmap discussion with the mentor before the program✅
✅
Enroll Our Career Transition Program on Data Science/AI/Machine Learning contains below topics
1. Induction Classes
2. Mastering Python from basics
3. Statistics, ML, NLP & Advanced ML
4. AI/MLOps/Streamlit & Heroku Deployment
5. CMLA for Data Science Lifecycle
6. Tableau
7. Excel
8. Power BI
9. Deep Learning[Feed Forward Neural Networks]
10. Computer Vision using Tensorflow
11. Forecasting
12. Transfer Learning
13. MySQL
14. Paid Internship with BEPEC on Data Science/AI
15. Data Science with R
16. AWS Sagemaker Studio
Key Takeaways:
1. Internship while learning the course
2. Paid Internship Opportunity while learning course(You need to crack the interview)
3. Unique Live Projects which increase your resume selection
4. 3+ POC which are mandatory for interviews
5. Customised Career Transition Roadmap based on learners' challenges
6. 100% Support until you get placed
7. Flexible entry & exit points, you can attend training any number of times until you get placed.
8. Mindmap Driven Learning for Revision and Easy Learning while Preparing for Interviews
11. Holistic Learning with 360+ Hours of Content
12. Tuition Classes on Weekdays
13. Weekend Live Classes on Saturday & Sunday
Instagram: https://www.instagram.com/meet_kanth/
Linkedin: https://www.linkedin.com/in/rajeev-kanth-6222a618a/
Spotify: https://open.spotify.com/show/0JDDBdl7aHtoBBwQuCyHV4
Check this out: https://linktr.ee/BepecSolutions
IT HELP DESK CLASSIFICATION using NLP + DL + ML + Data Augmentation
Everyone wants to be a Data Scientist/AI/Machine Learning/Data Analyst but are you learning company-demanded skills?
To get a job in Data Science/AI, One must build a portfolio.
✅Learners are wasting time than money due to improper roadmap on Data Science/AI
To speak with the mentor on Instagram @meet_kanth✅🔥
The only course which builds real-time experience in Data Science/Machine Learning/AI/Data Analytics🔥
Join our BEPEC Data Science/AI/Machine Learning Career Transition Program:
1-on-1 personalized roadmap discussion with the mentor before the program✅
✅
Enroll Our Career Transition Program on Data Science/AI/Machine Learning contains below topics
1. Induction Classes
2. Mastering Python from basics
3. Statistics, ML, NLP & Advanced ML
4. AI/MLOps/Streamlit & Heroku Deployment
5. CMLA for Data Science Lifecycle
6. Tableau
7. Excel
8. Power BI
9. Deep Learning[Feed Forward Neural Networks]
10. Computer Vision using Tensorflow
11. Forecasting
12. Transfer Learning
13. MySQL
14. Paid Internship with BEPEC on Data Science/AI
15. Data Science with R
16. AWS Sagemaker Studio
Key Takeaways:
1. Internship while learning the course
2. Paid Internship Opportunity while learning course(You need to crack the interview)
3. Unique Live Projects which increase your resume selection
4. 3+ POC which are mandatory for interviews
5. Customised Career Transition Roadmap based on learners' challenges
6. 100% Support until you get placed
7. Flexible entry & exit points, you can attend training any number of times until you get placed.
8. Mindmap Driven Learning for Revision and Easy Learning while Preparing for Interviews
11. Holistic Learning with 360+ Hours of Content
12. Tuition Classes on Weekdays
13. Weekend Live Classes on Saturday & Sunday
Instagram: https://www.instagram.com/meet_kanth/
Linkedin: https://www.linkedin.com/in/rajeev-kanth-6222a618a/
Spotify: https://open.spotify.com/show/0JDDBdl7aHtoBBwQuCyHV4
Check this out: https://linktr.ee/BepecSolutions
Listen to this Podcast to learn more about how to be a Successful Data Scientist.
Just focus on these 4 Important Skills
To learn more: CLICK HERE
Host: www.instagram.com/meet_kanth/
Whatsapp Us: +919121516181
Listen to this Podcast to learn more about best laptops for Data Science Learners.
To learn more : CLICK HERE
Host : www.instagram.com/meet_kanth/
Whatsapp Us: +919121516181
What actually is Data Science? Why learn Data Science? Who needs to learn Data Science? Is it worth Learning? What actually do Data scientists do?
To learn more : CLICK HERE
Host : www.instagram.com/meet_kanth/
Whatsapp Us: +919121516181
Everyone struggling with interview preparation, they are able to complete the course or college degree or MS. But everyone struggling with the interview preparation.
Holistic Learning Approach #1 Data Science Career Transition Program
with Data Scientist Job Simulation Environment.
We make career transitions fast & possible for any background.
✅ 100% Hike Guaranteed & Job Guaranteed Programs
✅ Mentor Support, even after getting placed as Data Scientist/ AI Engineer/ML Engineer
✅ 11+years Career Gap Learners got placed as Data Scientist
✅ Faculties got placed as Data Scientist with BEPEC Programs
✅ Non-Engineering Background, Non-Programming Learners Got placed as Data Scientists
REGISTER TODAY!! ( www.bepec.in )
That's Ok! To learn slow.
For more guidance message me over Instagram at @meet_kanth
Podcast hosted by www.bepec.in
How to be Unstoppable with Career or Life?
To know more about Podcast Speaker, Follow him on Instagram @meet_kanth
Podcast Hosted by BEPEC, www.bepec.in
Follow the solution to fix this problem of interview failure.
Everyone wants to be Data Scientist/AI/Machine Learning but are you learning company demanded skills??
✅To get a job in Data Science/AI, One must build a portfolio.
✅Learners are wasting more time than money due to improper roadmap on Data Science/AI
✅To speak with the mentor on Instagram: https://www.instagram.com/meet_kanth/
🔥The only course which builds real-time experience on Data Science/Machine Learning/AI/Data Analytics🔥
Join our BEPEC Data Science/AI/Machine Learning Career Transition Program:
✅Video one-on-one personalized roadmap discussion with the mentor before the program
✅Enroll to our Career Transition Program on Data Science/AI/Machine Learning contains the below topics
1. Induction Classes
2. Mastering Python from the basics
3. Statistics, ML, NLP & Advanced ML
4. AI/MLOps
5. CMLA for Data Science Lifecycle
6. Tableau
7. Deep Learning
8. Forecasting
9. MySQL
10. Paid Internship with BEPEC on Data Science/AI
11. Data Science with R & Julia
12. AIOps with Dynatrace
13. AWS Sagemaker Studio
Key Takeaways:
1. Internship while learning the course
-
Paid Internship Opportunity while learning course(You need to crack interview)
-
Unique Live Projects which increase your resume selection
-
3+ POC which are mandatory for interviews
-
Customised Career Transition Roadmap based on learner's challenges
-
100% Support until you get placed
-
Flexible entry & exit points, you can attend training any number of times until you get placed.
-
4 Examinations & One Final Examination with Video & Paper Based Submission
-
You get a "Certificate of Appreciation" based on your project work on Data Science Real-Time Projects
-
Community to work on Group Projects
-
50+ Assignments to work
-
Weekly Video Interview Preparation Sessions
Book your slots, before getting on the waiting list.
www.bepec.in/registration-form
Enjoy the Podcast on Simplifying Machine Learning #1
To speak with our Mentor Mr Kanth, Message him on Instagram
Do-Follow on Instagram: meet_kanth
❌Companies are not hiring freshers on Data Science/AI based on your course completion certificates.
✅To get a job in Data Science/AI, One must build a portfolio.
✅Learners are wasting time than money due to improper roadmap on Data Science/AI
✅To speak with the mentor on Instagram @meet_kanth
About BEPEC Data Science Career Transition Program:
✅Video one-on-one roadmap discussion with the mentor before the program
✅Enroll Our Career Transition Program on Data Science/AI contains for 100% Hike Guarantee:
1. Induction Classes
2. Mastering Python from basics
3. Statistics, ML, NLP & Advanced ML
4. AI/MLOps
5. CMLA for Data Science Lifecycle
6. Tableau
7. Deep Learning
8. Forecasting
9. MySQL
10. Paid Internship with BEPEC on Data Science/AI
11. Data Science with R & Julia
12. AIOps with Dynatrace
13. AWS Sagemaker Studio
Key Takeaways:
-
Internship while learning the course
-
Paid Internship Opportunity while learning course(You need to crack interview)
-
Unique Live Projects which increases your resume selection
-
3+ POC's which are mandatory for interviews
-
Customised Career Transition Roadmap based on learners challenges
-
100% Support until you get placed
-
Flexible entry & exit points, you can attend training any number of times until you get placed.
-
4 Examinations & One Final Examination with Video & Paper Based Submission
-
You get a "Certificate of Appreciation" based on your project work on Data Science Real-Time Projects
-
Community to work on Group Projects
-
50+ Assignments to work
-
Weekly Video Interview Preparation Sessions
-
Weekly Video Doubt Clarification Sessions
Book your slots, before getting on the waiting list.
www.bepec.in/registration-form
Thank you for sharing Valuable Info regarding how to prepare for Data Science.
To speak with our Mentor Mr Kanth, Message him on Instagram
Do-Follow on Instagram: meet_kanth
❌Companies are not hiring freshers on Data Science/AI based on your course completion certificates.
✅To get a job in Data Science/AI, One must build a portfolio.
✅Learners are wasting time than money due to improper roadmap on Data Science/AI
✅To speak with the mentor on Instagram @meet_kanth
About BEPEC Data Science Career Transition Program:
✅Video one-on-one roadmap discussion with the mentor before the program
✅Enroll Our Career Transition Program on Data Science/AI contains for 100% Hike Guarantee:
1. Induction Classes
2. Mastering Python from basics
3. Statistics, ML, NLP & Advanced ML
4. AI/MLOps
5. CMLA for Data Science Lifecycle
6. Tableau
7. Deep Learning
8. Forecasting
9. MySQL
10. Paid Internship with BEPEC on Data Science/AI
11. Data Science with R & Julia
12. AIOps with Dynatrace
13. AWS Sagemaker Studio
Key Takeaways:
-
Internship while learning the course
-
Paid Internship Opportunity while learning course(You need to crack interview)
-
Unique Live Projects which increases your resume selection
-
3+ POC's which are mandatory for interviews
-
Customised Career Transition Roadmap based on learners challenges
-
100% Support until you get placed
-
Flexible entry & exit points, you can attend training any number of times until you get placed.
-
4 Examinations & One Final Examination with Video & Paper Based Submission
-
You get a "Certificate of Appreciation" based on your project work on Data Science Real-Time Projects
-
Community to work on Group Projects
-
50+ Assignments to work
-
Weekly Video Interview Preparation Sessions
-
Weekly Video Doubt Clarification Sessions
Book your slots, before getting on the waiting list.
www.bepec.in/registration-form
Thank you Sonam, For sharing your journey from Chemical Engineering to Machine Learning & Various views on NLP.
To speak with our Mentor Mr Kanth, Message him on Instagram
Do-Follow on Instagram: meet_kanth
❌Companies are not hiring freshers on Data Science/AI based on your course completion certificates.
✅To get a job in Data Science/AI, One must build a portfolio.
✅Learners are wasting time than money due to improper roadmap on Data Science/AI
✅To speak with the mentor on Instagram @meet_kanth
About BEPEC Data Science Career Transition Program:
✅Video one-on-one roadmap discussion with the mentor before the program
✅Enroll Our Career Transition Program on Data Science/AI contains for 100% Hike Guarantee:
1. Induction Classes
2. Mastering Python from basics
3. Statistics, ML, NLP & Advanced ML
4. AI/MLOps
5. CMLA for Data Science Lifecycle
6. Tableau
7. Deep Learning
8. Forecasting
9. MySQL
10. Paid Internship with BEPEC on Data Science/AI
11. Data Science with R & Julia
12. AIOps with Dynatrace
13. AWS Sagemaker Studio
Key Takeaways:
-
Internship while learning the course
-
Paid Internship Opportunity while learning course(You need to crack interview)
-
Unique Live Projects which increases your resume selection
-
3+ POC's which are mandatory for interviews
-
Customised Career Transition Roadmap based on learners challenges
-
100% Support until you get placed
-
Flexible entry & exit points, you can attend training any number of times until you get placed.
-
4 Examinations & One Final Examination with Video & Paper Based Submission
-
You get a "Certificate of Appreciation" based on your project work on Data Science Real-Time Projects
-
Community to work on Group Projects
-
50+ Assignments to work
-
Weekly Video Interview Preparation Sessions
-
Weekly Video Doubt Clarification Sessions
Book your slots, before getting on the waiting list.
www.bepec.in/registration-form
How to start with Data Scientist? Listen to this entire podcast!
✅ Please don't join Data Science based on Hype & Salary.
✅ Remember one thing, Watch videos on Data science is completely different from working on live Data Science Projects.
✅ Check out the difference between Course Project vs Real-Time Project: https://www.instagram.com/p/CPXOxjNDXyH/?utm_medium=copy_link
✅ Book free call consultation with Kanth: https://www.bepec.in/registration-form
BEPEC hosted Podcast with Shubham Khandelwal Data Scientist with 4+years of experience in The Math Company.
Thank you Shubham for your time & great insights for learners who are planning career in the field of Data Science.
Book a free call consultation on your career roadmap: https://www.bepec.in/registration-form
Speak with our mentor Mr Kanth on Instagram @meet_kanth
"We make career transitions fast & possible for any background."
-
We placed freshers with 4-8LPA Salary as Data Scientist
-
We placed learners with a gap of 11 years with salary 11LPA salary as Data Scientist
-
We placed 5 years of experience in mechanical to Data Science with a 15LPA salary as a Data Scientist
-
We placed 5 years experienced Database Admin with 17LPA salary as Data Scientist
-
We placed 10 years experience in Testing with 25LPA Salary as Data Scientist.
-
We placed 15+ years experience in mechanical & process excellence with 40LPA Salary as AI Engineer
Book a free call consultation & Get customized Career Transition Roadmap: https://www.bepec.in/registration-form
Find our mentor on Instagram @meet_kanth
Many machine learning models tend to be black boxes, where explainability is very limited, which can make it difficult to understand why a model is not performing as expected. This is especially true with regard to how a model performs over time with new training data.
The machine learning lifecycle begins with data warehousing, ETL pipelining, and model training. The next stages in the lifecycle: deployment, management, and operations. Machine learning deployment plays a critical part in ensuring a model performs well, both now and in the future, but it is also vitally important to understand model monitoring and model drift to that same end
We from BEPEC are ready to help you and make you shift your career at any cost
Book a free call consultation & Get customized Career Transition Roadmap: https://www.bepec.in/registration-form
Check our Instagram page: https://www.instagram.com/bepec_solutions/
Listen to this podcast to know why companies hire Data Scientists.
Data Scientist are analytical experts who utilize their skills in both technology and social science to find trends and manage data.
Data Scientist is someone who makes value out of data. Data scientist duties typically include creating various machine learning-based tools or processes within the company, such as recommendation engines or automated lead scoring systems. People within this role should also be able to perform statistical analysis.
We from BEPEC are ready to help you and make you shift your career at any cost
Book a free call consultation & Get customized Career Transition Roadmap: https://www.bepec.in/registration-form
Check our Instagram page: https://www.instagram.com/bepec_solutions/
"We make career transitions fast & possible for any background."
-
We placed freshers with 4-8LPA Salary as Data Scientist
-
We placed learners with a gap of 11 years with salary 11LPA salary as Data Scientist
-
We placed 5 years of experience in mechanical to Data Science with a 15LPA salary as a Data Scientist
-
We placed 5 years experienced Database Admin with 17LPA salary as Data Scientist
-
We placed 10 years experience in Testing with 25LPA Salary as Data Scientist.
-
We placed 15+ years experience in mechanical & process excellence with 40LPA Salary as AI Engineer
Book a free call consultation & Get customised Career Transition Roadmap: https://www.bepec.in/registration-form
Find our mentor on Instagram @meet_kanth
Various challenges while switching to Data Science/AI as Experienced/Fresher:
1. Do I need to work as Fresher in the field of Data Science by diluting my previous experience?
2. My CTC going to be diluted if I switch to Data Science/AI? Or Do I get the salary hike?
3. After working for many years into other experience, Can I crack Data Science Interview? Can I survive in Data Science/AI/ML fied?
For all the above questions, Book a free call consultation & Get a customised career transition roadmap into the field of Data Science/AI: https://www.bepec.in/registration-form
Speak with our mentor Mr Kanth on Instagram @meet_kanth
Data Science Interview preparation is crucial in Data Science Career Transition, Check out the Data Science Interview preparation roadmap.
Get customised career transition & make career transition fast with BEPEC Career Transition Programs: https://www.bepec.in/data-science-career-transition
To speak with our mentor on Instagram: @meet_kanth
Everyone is struggling with career transition, what is the right way to do that?? Listen to this video which changes your entire view on career transition, learning courses, e.t.c.
For more help on your career roadmap or guidance ping me on Instagram @meet_kanth
Book a free call consultation on career transition roadmap on Data Science/AI/ML on Instagram of Mr Kanth @meet_kanth
ML math plays a crucial role for your Data Science/AI Interviews, Listen to this entire podcast and book a free call consultation for Data Science/AI Career Roadmap www.kanthh.com/callto-kanth
Ping Mr. Kanth on Instagram @meet_kanth
Career transition is all about what you sow so shall you reap.
Book a free call consultation on your career roadmap on Instagram @meet_kanth or visit my website https://www.kanthh.com/callto-kanth
About our Career Transition Programs, Co-Developed by Senior AI Engineers: Become a Machine Learning Engineer who can work from designing Machine Learning Solution Architecture, Data Understanding, Data Wrangling, Model Building, Model Evaluation and Model Deployment using Docker and Sagemaker
Q & A Session from Recently Placed Participants: https://www.youtube.com/watch?v=wUy6YWXYQ9w&t=4s
Get Free Course on “Statistics for Data Science Audio Book”: https://www.maaog.co.in/statistics-for-data-science-audio-book
Read our Machine Learning CaseStudy on Fitness : https://www.maaog.co.in/machine-learning-casestudy-in-fitness_ebook
Take Free Webinar on Career Transition Programs: https://www.bepec.in/webinar-registration-form
Worried about how to start with AI Career?? https://www.bepec.in/the-enroute-to-ai-career
For more video updates, subscribe our YouTube Channel: https://www.youtube.com/channel/UCn1USB9-5UqKJTSHd1JGcVw/?sub_confirmation=1
Let's look into what companies are looking for from Machine Learning.
Machine Learning Job Requirement -1:Knowledge of statistics, machine learning, programming, data modeling, simulation, and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make valuable discoveries leading to prototype development and product improvement.
Machine Learning Job Requirement -2:
- Works to design and develop analytical/ data mining/ machine learning models as part of data science solutions.
- Gather, evaluate and document business requirements, translate to data science solution definition, and ability to implement the solution on a Big Data platform.
- Ability to design and build an end-to-end prototype data science solution to a business problem in any specific sector/ function.
- Ability to support and guide end-to-end model lifecycle management Create model documentation as per client/ regulatory standards
Interested to look into Data Science Prototype - Click Here
I hope you gonna through above Job Descriptions, Once cross-check whether you have the confidence to work on every point mentioned from above JD's?? Do you have a clear understanding of the Data Scientist lifecycle and his role in the company? Or you are just thinking about Statistics, Python, Machine Learning and Accuracies can help you get a job as Data Scientist??
To speak in interviews, you must have a proven portfolio on Data Science Projects to Showcase in your resume as well as to speak damn confident in interviews.
If you are planning to learn a Data Science Program based on the above job requirements enroll for our Data Science Career Transition Program(YDSCT30) 30% Discount: https://www.bepec.in/data-science-career-transition
I thought of sharing my way of learning Machine Learning & Deep Learning Algorithms, How I prepare for Interviews. It going to help you I think so.
For any free guidance on your career transition roadmap towards Data Science/AI/ML, please book a free call consultation www.kanthh.com/callto-kanth
Follow me on my Instagram @meet_kanth
To increase your chances of getting hired into the company as the Data Scientist/AI Engineer, every learner must place below projects.
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Forecasting Live Projects using LSTMs, RNNs, Bidirectional RNNs, e.t.c.
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Text & Audio Related Projects using BERT, Attention-based Neural Networks, LSTMs
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Computer Vision Projects using CNNs and different types of CNNs
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ML Algorithms
So, to meet the current market demand with live projects in your Resume, To get the Live Projects to work and to place in your resume please contact +919121516181 or https://www.bepec.in/registration-form
Follow our Mentor Mr Kanth on Instagram @meet_kanth and book a free call consultation.
Meet our Mentor, Mr Kanth, on Instagram @meet_kanth & book a free call consultation on his Instagram page and construct your career transition roadmap.
About our Career Transition Programs, Co-Developed by Senior AI Engineers: Become a Machine Learning Engineer who can work from designing Machine Learning Solution Architecture, Data Understanding, Data Wrangling, Model Building, Model Evaluation and Model Deployment using Docker and Sagemaker
Q & A Session from Recently Placed Participants: https://www.youtube.com/watch?v=wUy6YWXYQ9w&t=4s
Get Free Course on “Statistics for Data Science Audio Book”: https://www.maaog.co.in/statistics-for-data-science-audio-book
Read our Machine Learning CaseStudy on Fitness : https://www.maaog.co.in/machine-learning-casestudy-in-fitness_ebook
Take Free Webinar on Career Transition Programs: https://www.bepec.in/webinar-registration-form
Worried about how to start with AI Career?? https://www.bepec.in/the-enroute-to-ai-career
For more video updates, subscribe our YouTube Channel: https://www.youtube.com/channel/UCn1USB9-5UqKJTSHd1JGcVw/?sub_confirmation=1
Let's look into what companies are looking for from Machine Learning.
Machine Learning Job Requirement -1:Knowledge of statistics, machine learning, programming, data modeling, simulation, and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make valuable discoveries leading to prototype development and product improvement.
Machine Learning Job Requirement -2:
- Works to design and develop analytical/ data mining/ machine learning models as part of data science solutions.
- Gather, evaluate and document business requirements, translate to data science solution definition, and ability to implement the solution on a Big Data platform.
- Ability to design and build an end-to-end prototype data science solution to a business problem in any specific sector/ function.
- Ability to support and guide end-to-end model lifecycle management Create model documentation as per client/ regulatory standards
Interested to look into Data Science Prototype - Click Here
I hope you gonna through above Job Descriptions, Once cross-check whether you have the confidence to work on every point mentioned from above JD's?? Do you have a clear understanding of the Data Scientist lifecycle and his role in the company? Or you are just thinking about Statistics, Python, Machine Learning and Accuracies can help you get a job as Data Scientist??
To speak in interviews, you must have a proven portfolio on Data Science Projects to Showcase in your resume as well as to speak damn confident in interviews.
If you are planning to learn a Data Science Program based on the above job requirements enroll for our Data Science Career Transition Program(YDSCT30) 30% Discount: https://www.bepec.in/data-science-career-transition
Course Data Scientist: He/She cares more about statistics, python, machine learning, NLP, Deep Learning, e.t.c. they do it just they know all the above topics so they are doing it.
Real-Time Data Scientist: He/She cares more about value, more about adding impacting to business/process with the help of data. To deliver the impact they may use statistics, python, machine learning, deep learning, NLP.
Listen to this entire video and post me which Data Scientist you want to hire?
Get Flat 30% Discount(YMLCT30) on your Machine Learning Program: https://www.bepec.in/machinelearningcourse
About our Career Transition Programs, Co-Developed by Senior AI Engineers: Become a Machine Learning Engineer who can work from designing Machine Learning Solution Architecture, Data Understanding, Data Wrangling, Model Building, Model Evaluation and Model Deployment using Docker and Sagemaker
Q & A Session from Recently Placed Participants: https://www.youtube.com/watch?v=wUy6YWXYQ9w&t=4s
Get Free Course on “Statistics for Data Science Audio Book”: https://www.maaog.co.in/statistics-for-data-science-audio-book
Read our Machine Learning CaseStudy on Fitness : https://www.maaog.co.in/machine-learning-casestudy-in-fitness_ebook
Take Free Webinar on Career Transition Programs: https://www.bepec.in/webinar-registration-form
Worried about how to start with AI Career?? https://www.bepec.in/the-enroute-to-ai-career
For more video updates, subscribe our YouTube Channel: https://www.youtube.com/channel/UCn1USB9-5UqKJTSHd1JGcVw/?sub_confirmation=1
Let's look into what companies are looking for from Machine Learning.
Machine Learning Job Requirement -1:Knowledge of statistics, machine learning, programming, data modeling, simulation, and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make valuable discoveries leading to prototype development and product improvement.
Machine Learning Job Requirement -2:
- Works to design and develop analytical/ data mining/ machine learning models as part of data science solutions.
- Gather, evaluate and document business requirements, translate to data science solution definition, and ability to implement the solution on a Big Data platform.
- Ability to design and build an end-to-end prototype data science solution to a business problem in any specific sector/ function.
- Ability to support and guide end-to-end model lifecycle management Create model documentation as per client/ regulatory standards
Interested to look into Data Science Prototype - Click Here
I hope you gonna through above Job Descriptions, Once cross-check whether you have the confidence to work on every point mentioned from above JD's?? Do you have a clear understanding of the Data Scientist lifecycle and his role in the company? Or you are just thinking about Statistics, Python, Machine Learning and Accuracies can help you get a job as Data Scientist??
To speak in interviews, you must have a proven portfolio on Data Science Projects to Showcase in your resume as well as to speak damn confident in interviews.
Data Science Course: How to join right data science course? What are various questions and doubts before joining any Data Science Course? Listen to this podcasts on Various questions one need to ask before joining Data Science Course. Kind of mindset to have before joining the program.
To enroll Kanth's Career Transition Programs on Data Science/Machine Learning/ Artificial Intelligence https://www.bepec.in/registration-form
To ping Mr Kanth on Instagram @meet_kanth
Get Flat 30% Discount(YMLCT30) on your Machine Learning Program: https://www.bepec.in/machinelearningcourse
About our Career Transition Programs, Co-Developed by Senior AI Engineers: Become a Machine Learning Engineer who can work from designing Machine Learning Solution Architecture, Data Understanding, Data Wrangling, Model Building, Model Evaluation and Model Deployment using Docker and Sagemaker
Q & A Session from Recently Placed Participants: https://www.youtube.com/watch?v=wUy6YWXYQ9w&t=4s
Get Free Course on “Statistics for Data Science Audio Book”: https://www.maaog.co.in/statistics-for-data-science-audio-book
Read our Machine Learning CaseStudy on Fitness : https://www.maaog.co.in/machine-learning-casestudy-in-fitness_ebook
Take Free Webinar on Career Transition Programs: https://www.bepec.in/webinar-registration-form
For more video updates, subscribe our YouTube Channel: https://www.youtube.com/channel/UCn1USB9-5UqKJTSHd1JGcVw/?sub_confirmation=1
Let's look into what companies are looking for from Machine Learning.
Machine Learning Job Requirement -1:Knowledge of statistics, machine learning, programming, data modeling, simulation, and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make valuable discoveries leading to prototype development and product improvement.
Machine Learning Job Requirement -2:
- Works to design and develop analytical/ data mining/ machine learning models as part of data science solutions.
- Gather, evaluate and document business requirements, translate to data science solution definition, and ability to implement the solution on a Big Data platform.
- Ability to design and build an end-to-end prototype data science solution to a business problem in any specific sector/ function.
- Ability to support and guide end-to-end model lifecycle management Create model documentation as per client/ regulatory standards
Interested to look into Data Science Prototype - Click Here
I hope you gonna through above Job Descriptions, Once cross-check whether you have the confidence to work on every point mentioned from above JD's?? Do you have a clear understanding of the Data Scientist lifecycle and his role in the company? Or you are just thinking about Statistics, Python, Machine Learning and Accuracies can help you get a job as Data Scientist??
To speak in interviews, you must have a proven portfolio on Data Science Projects to Showcase in your resume as well as to speak damn confident in interviews.
If you are planning to learn a Data Science Program based on the above job requirements enroll for our Data Science Career Transition Program(YDSCT30) 30% Discount: https://www.bepec.in/data-science-career-transition
Get Flat 30% Discount(YMLCT30) on your Machine Learning Program: https://www.bepec.in/machinelearningcourse
About our Career Transition Programs, Co-Developed by Senior AI Engineers: Become a Machine Learning Engineer who can work from designing Machine Learning Solution Architecture, Data Understanding, Data Wrangling, Model Building, Model Evaluation and Model Deployment using Docker and Sagemaker
Q & A Session from Recently Placed Participants: https://www.youtube.com/watch?v=wUy6YWXYQ9w&t=4s
Get Free Course on “Statistics for Data Science Audio Book”: https://www.maaog.co.in/statistics-for-data-science-audio-book
Read our Machine Learning CaseStudy on Fitness : https://www.maaog.co.in/machine-learning-casestudy-in-fitness_ebook
Take Free Webinar on Career Transition Programs: https://www.bepec.in/webinar-registration-form
***Worried about how to start with AI Career?? https://www.bepec.in/the-enroute-to-ai-career
For more video updates, subscribe our YouTube Channel: https://www.youtube.com/channel/UCn1USB9-5UqKJTSHd1JGcVw/?sub_confirmation=1
Let's look into what companies are looking for from Machine Learning.
Machine Learning Job Requirement -1:Knowledge of statistics, machine learning, programming, data modeling, simulation, and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make valuable discoveries leading to prototype development and product improvement.
Machine Learning Job Requirement -2:
- Works to design and develop analytical/ data mining/ machine learning models as part of data science solutions.
- Gather, evaluate and document business requirements, translate to data science solution definition, and ability to implement the solution on a Big Data platform.
- Ability to design and build an end-to-end prototype data science solution to a business problem in any specific sector/ function.
- Ability to support and guide end-to-end model lifecycle management Create model documentation as per client/ regulatory standards
Interested to look into Data Science Prototype - Click Here
I hope you gonna through above Job Descriptions, Once cross-check whether you have the confidence to work on every point mentioned from above JD's?? Do you have a clear understanding of the Data Scientist lifecycle and his role in the company? Or you are just thinking about Statistics, Python, Machine Learning and Accuracies can help you get a job as Data Scientist??
To speak in interviews, you must have a proven portfolio on Data Science Projects to Showcase in your resume as well as to speak damn confident in interviews.
If you are planning to learn a Data Science Program based on the above job requirements enroll for our Data Science Career Transition Program(YDSCT30) 30% Discount: https://www.bepec.in/data-science-career-transition
We are experts in transforming careers into Data science from any non-technical profile. We transformed close to 1000+ career transitions in the last 1 year and more than 50+ career transition even in this pandemic.
Our Data Science Career Transition Programs are unique from the industry. We make our learners speak with our mentor and our mentors understand their challenges and design the roadmap to their career transition.
Our trainers personally monitor our learners until they get placed into the industry as Data Scientist or AI Engineer. Every learner can speak with their trainers via Whatsapp or Direct call.
We take every learner from very basics like what is programming to working on Machine Learning, Deep Learning Model Deployments and working on different programming languages like R, Python, Spark, H20, Tensorflow, Keras, AWS Sagemaker, e.t.c.
We're hosting special batch on Data Science Career Program from 8th July @ 8.30 PM(IST) to 10 PM(IST).
We host our Career Transition Programs with Limited Slots. If anyone interested please book your slots by using the link in bio by 8th July 2020. (Special Discounts)
For Free Call Consultation with our trainer Mr.Kanth™️ - https://www.kanthh.com/callto-kanth
Link in bio: https://www.bepec.in/registration-form
Listen to our chat with Data Scientist, Shubham Mishra and below are the points we discussed in our "Chat with Data Scientists" show.
We discussed below points.
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Lifecycle as a Data Scientist & his challenges
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How is Data Science job profile going to be impacted in this pandemic?
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What is his journey towards Data Science role?
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Which programming language is he using?
To deliver more real-time knowledge to our learners and followers, we're hosting this show "Chat with Data Scientists".
For Free Call Consulting with our Mentor Mr.Kanth™️ - https://www.kanthh.com/callto-kanth
For Career Transition Programs on AI/ML & Data Science - https://www.bepec.in/ai
Listen to our podcasts in Spotify & iTunes - "Tech Podcasts on AI/ML
Subscribe to our youtube channel for more content on career transition - https://www.youtube.com/channel/UCn1USB9-5UqKJTSHd1JGcVw/?sub_confirmation=1
Hire a Mentor for Data Science and AI transition. You can hire me as your mentor for your career transition.24/7 support and guide you in every aspect. ☑️Join my "Data Science Interview Preparation Program" & hire me as your mentor until you get placed as Data Scientist. Registration link in description..
⛔️ Get Flat 30% Discount(YMLCT30) on your Machine Learning Program: https://www.bepec.in/machinelearningc...
About our Career Transition Programs, Co-Developed by Senior AI Engineers: Become a Machine Learning Engineer who can work from designing Machine Learning Solution Architecture, Data Understanding, Data Wrangling, Model Building, Model Evaluation and Model Deployment using Docker and Sage maker
⛔️ Q & A Session from Recently Placed Participants: https://www.youtube.com/watch?v=wUy6Y...
⛔️ Get Free Course on “Statistics for Data Science Audio Book”: https://www.maaog.co.in/statistics-fo...
⛔️ Read our Machine Learning CaseStudy on Fitness : https://www.maaog.co.in/machine-learn...
⛔️ Take Free Webinar on Career Transition Programs: https://www.bepec.in/webinar-registra...
For more video updates, subscribe our YouTube Channel: https://www.youtube.com/channel/UCn1U...
To speak in interviews, you must have a proven portfolio on Data Science Projects to Showcase in your resume as well as to speak damn confident in interviews.
If you are planning to learn a Data Science Program based on the above job requirements enroll for our Data Science Career Transition Program(YDSCT30)
⛔️ 30% Discount: https://www.bepec.in/data-science-car...
Check our Instagram page:
As the COVID-19 corona virus outbreak continues to spread across the globe, companies and researchers are looking to use artificial intelligence as a way of addressing the challenges of the virus. A number of research projects are using AI to identify drugs that were developed to fight other diseases but which could now be repurposed to take on corona virus. By studying the molecular setup of existing drugs with AI, companies want to identify which ones might disrupt the way COVID-19 works.
If you are planning to learn a Data Science Program based on the above job requirements enroll for our Data Science Career Transition Program(YDSCT30)
⛔️ 30% Discount: https://www.bepec.in/data-science-car...
We from BEPEC are ready to help you and make you shift your career at any cost.
For more details visit: https://www.bepec.in/
Bepec registration form : https://www.bepec.in/registration-form
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Digital Transformation is the use of new, fast and frequently changing digital technology to solve problems. One of the examples of digital transformation is cloud computing. It reduces reliance on user owned hardware and increases reliance on subscription based cloud services.
Digital transformation will bring success to you largely because of its speed and accuracy –especially when digital disruption are snapping at the heels of many businesses. Let’s explore the incredible benefits that digital transformation will bequeath on business and its workforce.
To speak in interviews, you must have a proven portfolio on Data Science Projects to Showcase in your resume as well as to speak damn confident in interviews.
If you are planning to learn a Data Science Program based on the above job requirements enroll for our Data Science Career Transition Program(YDSCT30)
⛔️ 30% Discount: https://www.bepec.in/data-science-car...
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A career change may also open you up to travel opportunities, and the chance to develop new skills and meet new people. If you have decided you would like to change careers, the first thing you will need to do is research. Get started by looking for job profiles, to find out more about what your chosen career involves and its entry requirements.
⛔️ Get Flat 30% Discount(YMLCT30) on your Machine Learning Program: https://www.bepec.in/machinelearningc...
About our Career Transition Programs, Co-Developed by Senior AI Engineers: Become a Machine Learning Engineer who can work from designing Machine Learning Solution Architecture, Data Understanding, Data Wrangling, Model Building, Model Evaluation and Model Deployment using Docker and Sage maker
⛔️ Q & A Session from Recently Placed Participants: https://www.youtube.com/watch?v=wUy6Y...
⛔️ Get Free Course on “Statistics for Data Science Audio Book”: https://www.maaog.co.in/statistics-fo...
⛔️ Read our Machine Learning CaseStudy on Fitness : https://www.maaog.co.in/machine-learn...
⛔️ Take Free Webinar on Career Transition Programs: https://www.bepec.in/webinar-registra...
For more video updates, subscribe our YouTube Channel: https://www.youtube.com/channel/UCn1U...
If you are planning to learn a Data Science Program based on the above job requirements enroll for our Data Science Career Transition Program(YDSCT30)
⛔️ 30% Discount: https://www.bepec.in/data-science-car...
Check our Instagram page: https://instagram.com/bepec_solutions/
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AI has increased in the last five years because new machine learning techniques are solving particular problems in ways that are similar to humans and with comparable accuracy like playing games (reinforcement learning), reading and understanding natural language (text analytics), and analyzing images and videos (convolutional neural networks or CNNs).
To speak in interviews, you must have a proven portfolio on Data Science Projects to Showcase in your resume as well as to speak damn confident in interviews.
If you are planning to learn a Data Science Program based on the above job requirements enroll for our Data Science Career Transition Program(YDSCT30)
⛔️ 30% Discount: https://www.bepec.in/data-science-car...
We from BEPEC are ready to help you and make you shift your career at any cost.
For more details visit: https://www.bepec.in/
Bepec registration form : https://www.bepec.in/registration-form
Check our Instagram page: https://instagram.com/bepec_solutions/
Check our Facebook Page : https://www.facebook.com/Bepecsolutions/
Check our youtube channel for more videos and please subscribe: https://www.youtube.com/channel/UCn1U...
Let's look into what companies are looking for from Machine Learning.
Machine Learning Job Requirement -1:
Knowledge of statistics, machine learning, programming, data modeling, simulation, and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make valuable discoveries leading to prototype development and product improvement.
Machine Learning Job Requirement -2 :
• Works to design and develop analytical/ data mining/ machine learning models as part of data science solutions.
• Gather, evaluate and document business requirements, translate to data science solution definition, and ability to implement the solution on a Big Data platform.
• Ability to design and build an end-to-end prototype data science solution to a business problem in any specific sector/ function. etc..
We from BEPEC are ready to help you and make you shift your career at any cost.
For more details visit: https://www.bepec.in/
Bepec registration form : https://www.bepec.in/registration-form
Check our youtube channel for more videos and please subscribe: https://www.youtube.com/channel/UCn1U...
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For any help or for any guidance please email enquiry@bepec.in
Major Difference between AI/ML Engineer & Data Scientist. Actually, there are multiple parameters you can differentiate these two professionals and if you are looking to hire machine learning engineer and shortlisting the data scientist you need to know the actual difference between these two AI specialists. Machine learning is a branch of artificial intelligence where a class of data driven algorithms enables software applications to become highly accurate in predicting outcomes without any need for explicit programming.
If you want to become a ML engineer you may have options like either continue working as entry level programmer or explore the opportunities into AI filed and become a specialist in big data or machine learning programmer to develop an AI model.
If you are ambitious to become a data scientist, you need to gain more education as master/doctorate degree to make your academic skills more strong and gain the capability to analyze and utilize the data for deep learning.
We from BEPEC are ready to help you and make you shift your career at any cost.
Anyone are interested for Career Transition Programs on ML / AI / DL / Data Science
get register here https://www.bepec.in/registration-form
For more details visit: https://www.bepec.in/
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Neural networks is one of the most powerful and widely used algorithms when it comes to the sub field of machine learning called deep learning. The neural networks that we are going to considered are strictly called artificial neural networks, and as the name suggests, are based on what science knows about the human brain’s structure and function.
Briefly, a neural network is defined as a computing system that consist of a number of simple but highly interconnected elements or nodes called Neurons , which are organized in layers which process information using dynamic state responses to external inputs. This algorithm is extremely useful, as we will explain later, in finding patterns that are too complex for being manually extracted and taught to recognize to the machine.
We from BEPEC are ready to help you and make you shift your career at any cost.
For more details visit: https://www.bepec.in/
Bepec registration form : https://www.bepec.in/registration-form
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These days, one of the biggest concerns in the corporate world is the need to grow in your job. As the corporate world is getting competitive every minute, many of us are trying too hard to stay in the league.
You can also create enough opportunities by building a network within your workplace. Venture out with your team lead and coworkers often, strike healthy conversations at lunch, or call for quick meetings during break times. Discussing official as well as unofficial ideas can help you setup a structured network.
We from BEPEC are ready to help you and make you shift your career at any cost.
Anyone are interested for Career Transition Programs on ML / AI / DL / Data Science
get register here https://www.bepec.in/registration-form
For more details visit: https://www.bepec.in/
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Q & A Session with Recent placed participants. Thank you Swetha & Lakme for your advice to our learners & making the Data science Interview Preparation session wonderful!! To Know More Join Our Career Transition Program Enroll now!! call @9121516181
We from BEPEC are ready to help you and make you shift your career at any cost.
Anyone are interested for Career Transition Programs on ML / AI / DL / Data Science
get register here https://www.bepec.in/registration-form
For more details visit: https://www.bepec.in/
Check our youtube channel for more videos and please subscribe: https://www.youtube.com/channel/UCn1U...
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As demand for data scientist skills remains strong, hiring for these positions poses a challenge.
Data science overlaps with the growing field of artificial intelligence (AI). To function at their full potential, AI applications require data lots of it. In fact many of the following AI and data science skills from programming languages to algorithmic techniques work in tandem with one another r building on top of each other to garner deeper data insights. Consequently, as the demand for data scientists increases the discipline presents an enticing career path for students and existing professionals.
We from BEPEC are ready to help you and make you shift your career at any cost.
Anyone are interested for Career Transition Programs on ML / AI / DL / Data Science
get register here https://www.bepec.in/registration-form
For more details visit: https://www.bepec.in/
Check our youtube channel for more videos and please subscribe: https://www.youtube.com/channel/UCn1U...
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Are you looking to get a break in data science but struggling to clear interviews? There’s a ton of variance in interview questions. You will get the IBM interview process which from what we have heard is really high level questions like, describe how a decision tree works? or Describe how this works or that works?
You should think about the interview process as being similar to an important test at school: if you walk into interview without preparing, you are probably going to be in trouble. When answering any interview question you should have three goals in mind Be clear, Be concise and Answer appropriately. Mastering the first, be clear, is mostly about preparation. You can only explain something clearly when you know what you’re talking about. Being concise is about carefully listening to and answering the question, but not more and Answering appropriately just requires you keep in mind who you’re talking to. Are you speaking to a data scientist with 15 years of experience? and use as much jargon as you want.
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Major Assets of an AI Engineer, AI Engineers build, test, and deploy AI models as well as maintain the underlying AI infrastructure. They are problem solvers who can navigate between traditional software development and machine learning implementations.
In a nutshell, machine learning is a relatively novel approach at solving some problems in the computer science that were traditionally hard to solve such as for example, building a program that will successfully recognize handwritten text. Machine learning is founded on algorithms that parse large sets of data and learn from this data, without being programmed in the traditional sense of the word that is without relying on a series of steps but rather learning from the data that is fed into machine learning algorithms.
An AI Engineer also needs to understand both traditional and agile approach in software development life cycle including continuous integration, continuous delivery and continuous deployment (CI/CD). They also must understand various testing practices including test driven development and behavior driven development.
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There are many skills under the umbrella of data science, and we should not expect any one single person to be a master of them all. To become a data scientist requires a candidate to possess expert skills in various fields like software development, database query languages, machine learning, programming, mathematics, statistics, data visualization, etc. This seems like a lot and many do get discouraged once they go through this immense list of skills that they are told is necessary to become a data scientist.
This learning enables the program to think, decide and do work based on programmed instruction sets. The prerequisites for learning exciting Artificial Intelligence technologies are Strong hold on Mathematics,Strong experience of programming languages,Writing algorithm for finding patterns and learning,strong data analytics skills,Good knowledge of Discrete mathematics and Strong will to learn machine learning languages.
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Are you looking to get a break in data science but struggling to clear interviews? Well the process starts right from the stage you start researching the different roles that interest you. And it goes all the way up to the completion of in person interviews.
If you’re applying to hundreds of jobs and not getting any interviews, though, there’s a good chance that something is wrong. It could be that you’re not qualified for the jobs you are applying to or it could be that something in your application materials is bothering recruiters. To make matters more complicated, unlike software development positions which have more standardized interview processes, data science interviews can have huge variations. This is partly because as an industry, there still isn’t an agreed upon definition of a data scientist into three paths: Algorithms, Inference and Analytics.
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Machine Learning’s inroads into our collective consciousness have captured our imaginations. If you are interested in learning machine learning skills to enter this field, your moment is now. Majorly there are 4 properties or characteristics or measurements scales decide the whole depth and breadth of a machine learning project.
The key distinction has to do with the end goal. As a Data Analyst, you’re analyzing data in order to tell a story and to produce actionable insights for members of your team. The analysis is performed and presented by human beings to other human beings who may then go on to make business decisions based on what’s been presented. The “audience” for your output is human. As a Machine Learning engineer on the other hand, your final “output” is working software (not the analyses or visualizations that you may have to create along the way), and your “audience” for this output often consists of other software components that run autonomously with minimal human supervision.
The world is unquestionably changing in rapid and dramatic ways, and the demand for Machine Learning engineers is going to keep increasing exponentially. If this is YOUR future, then there’s no time like the present to start mastering the skills and developing the mindset you’re going to need to succeed.
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What are AI interview Questions?? (2020). Artificial Intelligence is positively impacting the market, nearly every large business is on the lookout for AI professionals to help them make their vision a reality.
Over the last decade, artificial intelligence (AI) has grown from a pipe dream into the driving force behind the fourth industrial revolution. If you browse through the world’s leading job boards, you will find that its at the heart of some of the most in-demand tech careers today. Everyone is trying to figure out ways to optimize their businesses and their practices and how to automate and make their day-to-day lives a little bit easier (or) a little bit more productive and functional. So whether your next job interview is related to data science, machine learning (ML) or deep learning (DL) you can bet that artificial intelligence questions will come up.
AI questions will keep popping up in various job interview scenarios. To make it easier for you to navigate through this space we have curated a list of questions about artificial intelligence and divided them into multiple categories. So are you hoping to move up the data science career ladder or looking to start your first machine learning internship, make sure that you brush up on these AI interview questions and answers so you can walk into your next interview oozing confidence.
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Getting a JOB that doesn't matter!!!! It's easy to get placed as a Data Scientist, After getting the job Who the people are surviving in their job roles that's the matter... Once you placed in a job now the real game starts... You have to deal with real-time projects and everything should be in reality there are no trails or chances to rectify your problems and issues and real-time challenges. Here in our career transition program, we give a clear picture of all The END to END real-time challenges in the Data Science job life cycle.
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Machine Learning is a field that has crazy advancements in the past couple of years. This trend and advancements have created a lot of Job opportunities in the industry. The need for Machine Learning Engineers are high in demand due to evolving technology and generation of huge amounts of data like Big Data. Reinforcement learning is an area of Machine Learning, It's about taking suitable action to maximize reward in a particular situation and is to be employed by various software and machines to find the best possible behavior that it should take in a specific situation. Reinforcement learning differs from the supervised learning in a way.
In supervised learning the training data has the answer key with it so the model is trained with the correct answer itself whereas in reinforcement learning there is no answer but the reinforcement agent decides what to do to perform the given task. In the absence of training data set it bounds to learn from its experience. There are two important learning models in reinforcement learning :
(a) Markov Decision Process. (b) Q-learning
Reinforcement learning solves a different kind of problem. In reinforcement learning, there is an agent that interacts with a certain environment, thus changing its state and receives rewards (or) penalties for its input. It's goal is to find patterns of actions by trying them all and comparing the results that yield the most reward points.
One of the key features of reinforcement learning is that the agents actions may not affect the immediate state of the environment but it impacts the subsequent ones.
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Data science is the study of data and it involves the developing methods of recording, storing, and analyzing data to effectively extract the useful information. Being a Data Scientist is one of the hottest and trending career option of decade. The demand for data scientist is huge,the number is said to be much bigger than the available candidates. Data Scientist help companies interpret and manage data and solve complex problems using expertise in a variety of data niches.
They generally have a foundation in computer science,modeling,statistics,analytics and math coupled with strong business sense.In large companies a data scientist works on the same problem for several months or even years. He/she only need to concentrate on the modelling of the data, and the mathematics or the statistics involved that goes into the model, because the employees of other are working on the certain specified jobs needed like engineering the data ingest, storage and production deployment. Fresher on the other hand, make the data scientist’s work uncertain and they work on multiple problems which can be of different domains at the same time.
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If you are looking to transition your career to data science, don't immediately start learning Python or R. Instead, leverage the domain expertise you have accumulated over the years. This
approach makes complete career transition. If you are coming from a non-technical background the easiest way to get started in data science is to take a domain knowledge focused approach.
Data Scientist is someone who makes value out of data. Data scientist duties typically include creating various machine learning-based tools or processes within the company, such as recommendation engines or automated lead scoring systems.
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A data scientist is a mathematician, a statistician, a computer programmer and an analyst equipped with a diverse and wide-ranging skill set, balancing knowledge in different computer programming languages with advanced experience in data mining and visualization.The cyclical nature of the data science life cycle is dependent on topic expertise, which is both the start and end of any data science project. When someone has expertise in a topic, they tend to want to know even more about it, which leads to asking questions.
Data Scientist is someone who makes value out of data. Data scientist duties typically include creating various machine learning-based tools or processes within the company, such as recommendation engines or automated lead scoring systems.
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Unsupervised learning is a machine learning technique, where you do not need to supervise the model, Unsupervised learning algorithms allows you to perform more complex processing tasks compared to supervised learning. Even, unsupervised learning can be more unpredictable compared with other natural learning methods.
While the demand for ML is growing, the underlying problem-description, skill sets required, or the people applying for these jobs are likely to look largely similar to what it is today.
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The Exact Euphoria of a Data Scientist!!
Data scientists can be real change-makers within an organization, offering insight that can illuminate the company’s trajectory toward its ultimate business goals.The major skill to be a data scientist implementing the concepts and algorithms to impact a business. Data Science been one of the buzz word across the industries. Every company now a days they are switching into Data Science.More over he/she need to build the data by applying skills and operations.
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AI Career Transition Skill set for 15+ experienced!!
One of the important factor for career transition towards AI is to have right skill set in your resume.The demand of AI skills has more than doubled over the past three years, and the number of job postings is up by 119 percent. However, job-seeker interest in artificial intelligence careers seems to have leveled off. This suggests that employers are going to struggle to fill these positions for many years.
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Artificial intelligence (AI) is an emerging technological trend. Artificial Intelligence (AI) technology has been gaining popularity in recent years. From robots serving food in restaurants to self-driving cars, these applications of artificial intelligence can be seen in our day-to-day lives.If you’re evaluating career options in this emerging field, look at these top five jobs in artificial intelligence and the skills that you’ll need to transition into these roles.
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Data science is arguably the hottest career of the 21st century. There are many paths to landing a career in data science, but for all intents and purposes, it is completely impossible to launch a Data Science career in the field without a college education. You will, at the very least, need a four-year bachelor’s degree. Keep in mind, however, that 73% of the professionals working in the industry have a graduate degree and 38% have a PhD. If your goal is an advanced Data Scientist leadership position, you will have to earn either a master’s degree or doctorate.
Data Scientist is someone who makes value out of data. Data scientist duties typically include creating various machine learning-based tools or processes within the company, such as recommendation engines or automated lead scoring systems.
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How to take your first steps down the Artificial Intelligence, Deep Learning, Machine Learning, career path, hiring managers will likely require that you hold at least a bachelor's degree in mathematics and basic computer technology. However, for the most part, bachelor's degrees will only get you into expert level positions.
While the demand for ML is growing, the underlying problem-description, skill sets required, or the people applying for these jobs are likely to look largely similar to what it is today.
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Data Science specialist, surveyed to identify what are the most-wanted Data Science skills that will give you the top-row ticket in your dream company. The experts analyzed more than 3500 job positions on the popular professional website, LinkedIn.com for data science jobs and created a report with the real-time data. It has listed top 21 individual skills that are most frequently expected from a data science professional.
Data Scientist is someone who makes value out of data. Data scientist duties typically include creating various machine learning-based tools or processes within the company, such as recommendation engines or automated lead scoring systems. People within this role should also be able to perform statistical analysis.
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Data Science case study on eye hospital programs like, Healthcare analytics have the potential to reduce costs of treatment, predict outbreaks of epidemics, avoid preventable diseases and improve the quality of life in general.
Data Science Career Transition if one of your goals as a data scientist is to learn new skills continuously, When it comes to long term goals, as you move up the data science ladder, being in a leadership position often means your role will be less technical. Choosing the right ones will, in turn, help you achieve your goals should you aspire to reach a position.
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The extreme main skill that any Machine Learning Engineer should have – more than the art of storytelling – is the art of questioning and analyzing the information in hand. The very first mistake that I did before getting into business analytics was failing to understand what “Business analytics” professional do in their work – at least its literal meaning. My cluttered mind strongly correlated “Business analytics” with the term “Business analysis”. At the end of my first day class, one thing I really understood was. The decision to join the business analytics program was taken based on the gut feeling, rather than an informed decision.
People within this role should also be able to perform statistical analysis.
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How to speak in data science, Machine Learning, AI Interviews,Are you looking to get a break in data science but struggling to clear interviews? You might even know the data science tools and techniques relevant to the job. And yet the employers keep rejecting you. I have a rich background in learning and development, a non-technical and non-data science field. The BEPEC career transition program helps to full fill your job dream, It took me months of hard work and disciplined effort, and numerous botched interviews, before finally landing a data science role here at BEPEC.
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Data Science jobs are the highest paid in the IT industry. In the past years, a barrage of data science roles came our way, so it is difficult to get a basic understanding of what they are and how they differ. Machine learning There is a considerable need for Data Scientist. Demand for Data Scientist is on the peak and they are among the highest paid people with the median base salary of $130,000 in America itself.There is a considerable need for Data Scientist. Demand for Data Scientist is on the peak and they are among the highest paid people with the median base salary of $130,000 in America itself.
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Data science important skill requires a diverse set of skills. Data scientists may benefit from a diverse skill-set that enables them to both crunch the numbers and effectively influence senior positions.Because data scientists focus on using data to influence and inform real-world decisions, they should be able to bridge the gap between numbers and actions. This requires skilled communication and an understanding of the business implications of their recommendations.his requires skills that go beyond the data, statistics and tools that data scientists use.
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Best way to prepare As for short-term goals, something to keep in mind is that you might not always have a lot of time to devote to learning new technical skills especially if your team demands lots of focus on higher-level goals. Data Science Career Transition if one of your goals as a data scientist is to learn new skills continuously, When it comes to long term goals, as you move up the data science ladder, being in a leadership position often means your role will be less technical. Choosing the right ones will, in turn, help you achieve your goals should you aspire to reach a position.
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Majority of people are focusing on career transition in Data Science, AI, Machine Learning. Building a career transition the very important thing you need to build confidence. There are two ways your job search needs focus. Certainty about what you want to do next and clear goals and actions for how you are going to achieve your targeted job. Before you begin your job search or even after you’ve started, be sure to answer these important elements of career transition:
What do you want to do next?
What is important to you in your next job?
What companies hire for those positions you are seeking?
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Data scientists position, as only appropriate preparation and preparation will get you cracking and performing well on the big day. Interview preparation program is require for all Data Scientists. If you are an aspiring Data scientist, you are expected to have a working knowledge, or understanding, or the capability to perform over multiple firms, with a bag full of skills. Data scientist is viewed as someone who can bridge the gap between multiple features of a business.
So it is not expected or required of you to be a specialist in all the aspects, but you should be able to link the features, idea and provide solutions across domains. To stand apart in an interview you should not only show your individual strength and domain expertise but come across as a person with enough management skills, along with good communication and technical skills who can blend and get to the crux of a problem.
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The massive amount of attention being paid to data scientists has only highlighted the uncertainty around the precise responsibilities the job entails. Now a days people are learning Data science but they don't know how to crack job. Separate job roles have been grouped under the data scientist umbrella, causing unnecessary confusion during the hiring process — and sometimes preventing companies from hiring the candidate they actually need.Making data accessible to data scientists and analysts in databases, potentially including streaming data. They may also work with Type B data scientists to integrate models into production.
Main tools: Python/Java/Scala, SQL, Spark, Airflow/Jenkins, cloud computing, Docker
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So here are the tensor flow skills which are must for both Machine learning and Deep learning.
Why Tensor Flow is an open-source software library built for deep learning or artificial neural networks. Tensor Flow skill is must for both ML & DL , you can create neural networks and computation mod else using flow graphs. It is one of the most well-maintained and popular open-source libraries available for deep learning. The Tensor Flow framework is available in C++ and Python. Other similar deep learning frameworks that are based on Python include theano ,Torch, Lasagne, Blocks, MXNet, pytorch, and Caffe. You can use Tensor Board for easy visualization and see the computation pipeline. Its flexible architecture allows you to deploy easily on different kinds of devices.
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We can summarize data science job life and jargon's job profile
Many questions are arising regarding, how to become a data scientist and what are the skills required. Here I’ll help you gain knowledge on how you acquire the skills of a data scientist. The challenge of becoming a Data scientist is that you need to obtain right skills and the profession demands a long list of skills to get hired.
Jargon is a literary term that is defined as the use of specific phrases and words in a particular situation, profession, or trade. These specialized terms are used to convey hidden meanings accepted and understood in that field.
Excellent communication skills means that you're able to convey information clearly, concisely, and convincingly in both written and verbal form. There's so much information-sharing that happens within companies to move projects along that employers can't afford to hire someone who isn't able to communicate their thoughts and ideas via email, in a presentation deck, or in a meeting.
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Object detection is a computer vision task that involves both localizing one or more objects within an image and classifying each object in the image. Sequence based object detection using mask RCNN is a challenging computer vision task that requires both successful object localization in order to locate and draw a bounding box around each object in an image. An extension of object detection involves marking the specific pixels in the image that belong to each detected object detection instead of using coarse bounding boxes during object localization. There are perhaps four main variations of the approach, resulting in the current pinnacle called Mask R-CNN.
R-CNN,Fast R-CNN,Faster R-CNN,Mask R-CNN. Mask R-CNN is a sophisticated model to implement, especially as compared to a simple or even state-of-the-art deep convolutional neural network model.
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We can summarize data science job life cycle with three major skills. Which covers three major skills on Data Science job profile.
Many questions are arising regarding, how to become a data scientist and what are the skills required. Here I’ll help you gain knowledge on how you acquire the skills of a data scientist. The challenge of becoming a Data scientist is that you need to obtain right skills and the profession demands a long list of skills to get hired.
Programming skills are required, no matter which role or company you’re interviewing for, you’re probably going to be presumed to know how to use the tools of the trade. This sounds like a database querying languages like SQL and a statistical programing language, like Python and R.
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Face Aging Using Conditional GANs (GANs) are extensions of the GANs model. You can read about Conditional GANs in my previous post here. In this post, I will try to explain how we can implement a GANs to perform automatic face aging. Face Aging GAN(Age-GANs) introduced by Grigory Antipov, Moez Baccouche, and Jean-Luc Dugelay, in their paper with titled Face Aging With Conditional Generative Adversarial Networks. The Face Aging-Gan has four networks.
An Encoder : It learns the inverse mapping of input face images and the age condition with the latent vector Z.
Encoder network generates a latent vector of the input images. The Encoder network is a CNN which takes an image of a dimension of (64, 64, 3) and converts it into a 100-dimensional vector.
There are four convolutional blocks and two dense layers.
Each convolutional block has a convolutional layer, followed by a batch normalization layer, and an activation function except the first convolutional layer.
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Spiking neural networks in Deep Learning, (SNNs) are inspired by information processing in biology, where sparse and asynchronous binary signals are communicated and processed in a massively parallel fashion. SNNs on neuromorphic hardware exhibit favorable properties such as low power consumption, fast inference, and event-driven information processing. This makes them interesting candidates for the efficient implementation of deep neural networks, the method of choice for many machine learning tasks. The goal of our review is to define a categorization of SNN training methods, and summarize their advantages and drawbacks. We further discuss relationships between SNNs and binary networks, which are becoming popular for efficient digital hardware implementation. Neuromorphic hardware platforms have great potential to enable deep spiking networks in real-world applications.
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Deep Learning was developed as a Machine Learning approach to deal with complex input-output mappings. While traditional ML methods successfully solve problems where final value is a simple function of input data. On the contrary, Deep Learning techniques are able to capture composite relations between air pressure recordings and English words, millions of pixels and textual description, brand-related news and future stock prices.
Basic definition of Deep Learning is a set of ML techniques that use stacked layers of transformation trainable from the beginning to the end. Performance is the main key difference between both algorithms. Although, when the data is small, Deep Learning algorithms don’t perform well. This is the only reason Deep Learning algorithms need a large amount of data to understand it perfectly.
Deep Learning is discovered and proves to have the best techniques with state-of-the-art performances. Thus, Deep Learning is surprising us and will continue to do so in the near future. Recently, researchers are continuous in exploring Machine Learning and Deep Learning. In the past, researchers were limited to academia. But, nowadays, research in ML and Deep Learning is making their place in both industries and academia.
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Choosing the appropriate forecasting technique to employ is a challenging issue and requires a comprehensive analysis of empirical results. Recent research findings reveal that the performance evaluation of forecasting models depends on the accuracy measures adopted. Some methods indicate superior performance when error based metrics are used, while others perform better when precision values are adopted as accuracy measures. As scholars tend to use a smaller subset of accuracy metrics to assess the performance of forecasting models, there is a need for a concept of multiple accuracy dimensions to assure the robustness of evaluation.
- Regression problems are supervised learning problems in which the response is continuous
- Linear regression is a technique that is useful for regression problems.
Classification problems are supervised learning problems in which the response is categorical.
Deep Learning techniques over regular data sets, tampered data sets and noisy data sets. First, Deep Learning techniques have been investigated over regular data sets, the experiments showed good results in terms of accuracy and error rate
Machine learning continues to be an increasingly integral component of our lives, whether we’re applying the techniques to research or business problems. Machine learning models ought to be able to give accurate predictions in order to create real value for a given organization.
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Data scientists are a new breed of analytical data expert who have the technical skills to solve complex problems – and the curiosity to explore what problems need to be solved.
Data science has over the past few years come a really long way. That is why they are integral part of understanding the working of many industries, however complex and intricate.Data science is taking on a big and prime role in functioning and growth process of brands. Being a data scientist is therefore a prime position for any person as they have the big task of managing data and providing solutions for their problems, both within and outside the organisation.
Data Scientist is someone who makes value out of data. Data scientist duties typically include creating various machine learning-based tools or processes within the company, such as recommendation engines or automated lead scoring systems. People within this role should also be able to perform statistical analysis.
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Markov chains are a fairly common, and relatively simple, way to statistically model random processes. They have been used in many different domains, ranging from text generation to financial modeling. A popular example is r/SubredditSimulator, which uses Markov chains to automate the creation of content for an entire subreddit. Overall, Markov Chains are conceptually quite intuitive, and are very accessible in that they can be implemented without the use of any advanced statistical or mathematical concepts. They are a great way to start learning about probabilistic modeling and data science techniques.
The Markov Chain is a model used to describe a sequence of consecutive events where the probability or chance of an event depends only on the event before it.If a sequence of events exhibits the Markov Property of the reliance on the previous state, then the sequence is called ‘Markovian’ in nature.
For some problems in Reinforcement Learning, the actions performed in a particular state is directly related to the previous state, the actions performed in that state and the rewards that the agent receives upon performing said actions.
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Machine Learning is one of the hottest career choices today. AI will create 2.3 million Machine Learning jobs by 2020, Emerging Jobs Report shows there are 9.8 times more Machine Learning Engineers working today than five years ago with 1,829 open positions listed on their site as of early 2018. Both Data Science and Machine Learning are generating more jobs than candidates right now, making these two areas the fastest growing tech employment areas today.
There can be many factors contributing to it. One of the reasons is the increasing popularity in the machine learning industry. Most companies are integrating ML and AI into their top data initiatives, which holds true for Indian companies as well. As more companies are investing in machine learning, they are looking to hire more ML experts for cutting-edge research.
While the demand for ML is growing, the underlying problem-description, skill sets required, or the people applying for these jobs are likely to look largely similar to what it is today. That being said, if we ask whether the appetite for complex models is growing, I think that in the short term, when a lot of organisations are still trying to splice data-driven decision making into their managerial DNA, the demand for basic skills and simpler models will dominate. Once most organisations have reached a certain level of analytical maturity, their appetite and ability to digest complex models will grow faster,
A data scientist is someone who can predict the future based on past patterns whereas a data analyst is someone who merely curates meaningful insights from data. A data scientist is expected to generate their own questions while a data analyst finds answers to a given set of questions from data.
The first thing I did as a data scientist is work on building out internal dashboards, basically surfacing information that we were tracking on the back end, but weren’t being used by the data analysts for any reasons. for example, we might have lacked the infrastructure to display it, or the data was just not very well processed. It really wasn’t anything tailored out from a customer need, but came from what I noticed the analyst team needed in order to do their job.
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At present, the world is going through another, possibly even stronger revolution: the use of artificial intelligence to perform complex cognitive tasks to solve business problems in ways that were previously either highly complicated or extremely resource-intensive.
Today, organizations must be innovative and leverage the latest technologies simply to stay in business. Enterprises that implement online retail, banking, and other services aren’t considering these channels as just another route to increase their revenue.
It is important to understand that to undergo digital transformation, companies may need to completely re-engineer their current processes to make use of technologies like the Internet of Things (IoT), Big Data analytics, artificial intelligence, and others instead of doing patchwork on existing processes to adapt to digital technologies. Furthermore, it is also important for senior IT executives to consider digital initiatives in tandem with their cloud strategy instead of treating them in isolation.
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We have nealry 15+ Machine learning algorithms, but entire machine learning can be summarised into 3 major machine learning equation which rule entire machine learning. Most of the people are learning machine learning courses and planning a career in machine learning. This podcast is pretty important to rule in space of machine learning.
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We can learn Data Science, Machine Learning & Deep Learning but making a career inside Data Science is pretty important. Here comes the question, how can i make my career in Data Science? How to build better career with Data Science? What type of interview questions going to come in data science? Which data science course is best? Listen to this podcast which helps you to build career in Data Science. Listen today!!!
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Career transition towards data science, machine learning, deep learning and ai. Majority of the professionals are planning to do career transition into this new technologies. But planning is different and actual live process of transition is different. Checkout this interesting podcast on "Various challenges we face while doing a career transition on machine learning"
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After completion of training most of the people don't know how to prepare for data science interviews or machine learning interviews. Always understanding what companies are expecting is pretty important while preparing for machine learning interviews. Preparing through free sources can help you to build knowledge on machine learning algorithms but preparation on real time projects is completely different. Learn the challenges of machine learning projects, go deep into machine learning algorithms, get expertise on python programming, stay with empathy on machine learning projects. Check this interesting podcast on 'How to prepare for Data Science & Machine learning interviews.
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Machine learning and Artificial intelligence been one of the best career's now. But when i'm working on six sigma after completion of mechanical engineering. 4 to 5 years back i came to know about machine learning, data science, artificial intelligence but doing to career transition 4 years back been pretty challenging very less resources and less understanding on what exactly data science? or what exactly machine learning? I can't figure out what exactly meant by machine learning algorithms, to say frankly i don't even know exact real time machine learning definition. To do career transition machine learning projects are important. but i don't know any machine learning projects.
Learn how i faced all the challenges and made my career on artificial intelligence. Check out this interesting journey.
The dawn of AI is upon us bringing even greater forms of automation into our lives. The world is concerned about what this new era might bring and all of this chatter brings uncertainty in nearly every field. All this to say that AI improvements will directly affect our ability to be creative as engineers. Let’s pull this attractive hype into reality with some real-world discussion.
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Most of the data science and machine learning learners are unable to pick right machine learning algorithm for their project. How to pick right machine learning algorithm classification, how to do machine learning algorithm comparison, any impact of deployment on machine learning algorithm for prediction. How to choose between advanced machine learning algorithms and supervised machine learning algorithms. To learn more about above questions refer this podcast.
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Do you know most of the people are failing to crack jobs on machine learning? They are learning huge amount of algorithms and they are good at programming even but still they are failing in machine learning interviews. Why they are failing in machine learning interviews? Check this podcast
We looked into various machine learning algorithms, deep learning e.t.c. all this algorithms can predict the things like yes or no and even some algorithms can do sequential predictions. But how can we do predictions on random events. Check this podcast to know more about motion planning in self driving cars.
Most of the professionals are switching towards AI from different sources. But how to start with AI is one the challenging issue. So this podcast can help you to get better view about AI and duration to get into AI job roles.
Various parameters which are important for getting into data science job roles. Check this video on how to prepare for machine learning interviews.
Behind every successful person witnessed failure. But they never stopped at failure, they learned from failures.
This podcast been one of the best thing ever done before. I think you gonna get good understanding on Data Science job role.
Data Science been one of the buzz word across the industries. Learn different ways to switch your career to Data Science
Learn about how statistics, data visualization, programming and machine learning are interlinked
While doing new course or developing new skill, which one is highly preferred. Is it certification or Project?