Becoming A Data Scientist: Recent Episodes
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Documenting my path from "SQL Data Analyst pursuing an Engineering Master's Degree" to "Data Scientist"
This week, I gave a talk at Valley TechCon in Harrisonburg, VA (where I live), which is a conference that features tech businesses and practitioners from the Shenandoah Valley of Virginia, and is in its 2nd year. There were a bunch of cool topics and speakers, and it was great to see what other great […]
In the first episode of the Becoming a Data Scientist podcast recorded in front of a live audience, Renee interviews Andrew Therriault - formerly the Director of Data Science for the Democratic National Committee & Chief Data Officer for the City of Boston, and currently Data Science Manager at Facebook - about how he learned data science, what advice he has for people who want to learn data science and apply for data science jobs, and about his career path as a Data Scientist and leader in the field.
Episode 17 Audio
I promised the audience at the RVATech Summit yesterday that I’d post the updated slides for my “Can a Machine be Racist or Sexist?” talk, so here they are! Here is the link to the previous post, which has a pdf version of the slides that’s almost identical, and a video from when I gave […]
The 2019 iteration of Tom Tom Fest (named after Thomas Jefferson) starts in under a month, and the Applied Machine Learning Conference (AMLC) is just over a month away, on April 11, in Charlottesville, VA! This is a conference I’ve helped plan since the beginning, and it’s grown in 3 years from a single theater […]
Hi, #APRADAS2018 Attendees! I plan to come back and add more info here in the future, but for now, here is a PDF version of my slides: My Journey from Advancement Data Analyst to Data Scientist
The purpose of the Summer of Data Science is to learn a specific topic or complete a specific project or read a book or finish a course so you can check something off of your long data science “to learn” list, and have fun achieving goals along with other data science learners during a fixed period of time. The deadline should be motivating, to get you to start and finish something before the summer is over.
Week 1 was all about brainstorming ideas and gathering resources – dreaming up what you’d love to learn, and finding content that will help you learn it.
Week 2 (which started yesterday, but don’t worry, jump in any time even if you see this a month from now) is all about goal-setting.
About a month ago, on a whim, I posted the #CraftyDataViz contest, hoping for some beautiful and wacky homemade visualizations, and you all sure came through! The entries were gorgeous and the judging was super difficult!
The main goal of the Summer of Data Science is to learn something new during a fixed period of time, and share your progress and references to help and inspire others (and to get help from and get inspired by others, too!).
Being as spontaneous as usual, I asked if anyone would be interested in having a #CraftyDataViz contest, and several people responded yes! So, here we are. Time to get creative!
I presented a talk with this title at the Applied Machine Learning Conference at Tom Tom Fest in Charlottesville (which I also helped plan) last Thursday April 12, 2018.
My interest in this topic started long ago, and I partially based this talk off of my blog post "A Challenge to Data Scientists" from 2015. There are a ton of links throughout, and I included the slide notes so you have those along with the presentation...
I’ve been telling everyone that I’d do something “data fun” when I hit 20K Twitter followers, so I posted an analysis of my podcast listeners! I used python and pandas in a Jupyter notebook for the first part, then I did a dashboard in Tableau for the last part.
I’m assuming that some people who see my talk at Demystifying Data Science conference will be dropping by here, so I wanted to put up a quick post summarizing some of the resources I have made available to data science learners!
Back before I had so many followers, and it was less stressful to put goofy stuff "in the wild", I wrote data science parody lyrics to "Summer of '69" and "For the Love of Money". Well, a while ago, another idea popped into my head..
- Sorry for the issues loading images and with logins on this site. I’ve had problems ever since I had bluehost set me up with HTTPS certificates, and apparently those certificates have expired or something and are causing issues with the images being able to load, etc. I’ll look into it, but I also have […]
I was just pondering some ways to discuss machine learning terminology in a way that would be accessible to beginners, and figured I'd share my semi-thought-out ideas here. I'm sure this has been done before, but here are some common machine learning terms couched in the language of cooking and food. Feedback welcome!
Machine Learning Algorithm
A machine learning algorithm is a list of instructions to guide a computer to analyze some data to find patterns, and works much like a cooking recipe. You put some data in (ingredients), do some stuff to it (preparation and cooking), and then evaluate how the results compare to what you were hoping to accomplish (photo in your cookbook and expectations of taste).
Since Memorial Day in the U.S. is the unofficial start of the summer season, I figured today would be a good time to launch the SUMMER OF DATA SCIENCE 2017!!!
The Summer of Data Science is a commitment to learn something this summer to enhance your data science skills, and to share what you learned.
Quick note for those of you who follow me on Flipboard. I added another one, seeded with links from my Challenge to Data Scientists article, on Bias in Machine Learning. Enjoy!
Renee interviews Randal S. Olson, Senior Data Scientist in the Institute for Biomedial Informatics at UPenn, about his path to becoming a data scientist, his interesting data science blog posts, and his work with non-data-scientists and students. Podcast Audio Links: Link to podcast Episode 16 audio Podcast's RSS feed for podcast subscription apps
The Becoming a Data Scientist tees are ready to sell! I ordered a couple myself before posting them for sale, to make sure the quality was good. They came out great!! And if you order from Teespring before ~~March~~April 1 using this link: Becoming a Data Scientist Store – Free Shipping, you’ll get free shipping on your order! The design is a combination of those submitted to our contest by Amarendranath “Amar” Reddy and Ryne & Alexis.
David Meza is Chief Knowledge Architect at NASA, and talks to Renee in this episode about his educational background, his early work at NASA, and examples of his work with multidisciplinary teams. He also describes a project involving a graph database that improved search capabilities so NASA engineers could more easily find "lessons learned".
Podcast Audio Links: Link to podcast Episode 15 audio Podcast's RSS feed for podcast subscription apps
I still haven't heard from one of the 3 finalists, but I wanted to go ahead and post the first two, and I'll update here with the final one later. These finalists win a data science book and a t-shirt, and I'll choose from the three (I'm actually considering combining elements from two of them!) and announce the final t-shirt design when they are available for sale.
Without further ado, the top 3 vote-winners after 94 votes, in no particular order, are....
In this first episode of "Season 2" of Becoming a Data Scientist podcast, we meet Jasmine Dumas, a new data scientist who tells us about going from biomedical engineering into a data science project experience and then finding her first job as a data scientist.
Podcast Audio Links: Link to podcast Episode 14 audio Podcast's RSS feed for podcast subscription apps
Which of these awesome designs would you like on your future Becoming a Data Scientist T-Shirt? You all will narrow it down to 3, then I’ll pick the final winner to be printed! For the ones that aren’t t-shirt-print-ready, I’ll get a graphic designer to tidy them up, so don’t worry about whether they’re printable […]
I need a part-time remote assistant to help keep my websites up to date, among other things! Thanks to my generous Patreon supporters, I can hire someone to help me out 8-20 hours per month, paying $15/hr. More info and application form at this link. Please let me know if you have any questions or […]
In this audio-only special Becoming a Data Scientist Podcast episode, I interview Dr. Ed Felten, Deputy U.S. Chief Technology Officer, about the Future of Artificial Intelligence (from The White House!).
I want to hire some people to help me update my websites more frequently, do the maintenance stuff, and to help edit the podcast so I can produce episodes more frequently. I outlined my whole plan here on my Patreon Campaign. You’ll see a new page on this site soon acknowledging supporters, and I’ll update […]
I’ve decided that I want to have Becoming a Data Scientist t-shirts to sell and to give out to podcast guests and contest winners, but I am not a graphic designer, so I need some help! So I’m going to have a t-shirt design contest!
Becoming a Data Scientist podcast, Partially Derivative podcast, Adversarial Learning podcast, and some other awesome data people that do elections forecasting for their day jobs joined together for this talk about the US election and the subsequent major questions surrounding the predictions, since basically all of them heavily leaned toward a different overall outcome than we got. If you're interested at all in data science surrounding political campaigns, this episode is a must-listen!
I just got back from PydataDC, where I learned a lot, had fun, and met a bunch of awesome people! I’ll definitely write about it more later, but I wanted to share my slides here since I told the attendees they could find them on my website. I got good feedback on the talk, and […]
Here is the 1st batch of results from the Becoming a Data Scientist Survey. Because of the sample size and unscientific casual nature of this survey, we can't make any broad generalizations about the industry from these results, but you can see some general preliminary trends in the breakdowns that would be interesting to study more.
95% of the 158 respondents who gave answers about their jobs follow at least one of my twitter accounts, so you can think of these results as representing my twitter followers.
I'm mostly going to let the tables and graphs speak for themselves...
It’s been brought to my attention that iTunes only shows the last 10 episodes of the Becoming a Data Scientist Podcast. If you haven’t seen/heard episodes 0-3, you can ...
I am collecting information about my “audiences” so I can improve my websites, podcast, and also formulate a plan for a Patreon campaign to generate funds for getting help and to free myself up to create more content. Please fill out the survey and share it with your friends and followers on social media! The […]
Boosting ensemble algorithms in Machine Learning use an approach that is similar to assembling a diverse team with a variety of strengths and experiences. If machines make better decisions by combining a bunch of “less qualified opinions” vs “asking one expert”, then maybe people would, too.
In this interview, we meet physicist Debbie Berebichez, who you might recognize from her TEDx talks, her appearances in Discovery Channel’s Outrageous Acts of Science and other TV shows! Debbie grew up in Mexico City and was discouraged by her family and teachers from studying science, but later went on to become the first Mexican woman to get a PhD in physics from Stanford, and is now Chief Data Scientist at Metis Data Science Bootcamp in New York. Podcast Audio Links: Link to podcast Episode 13 audio Podcast's RSS feed for podcast subscription apps
Verena, David, Kerry, and Anthony are members of the Becoming a Data Scientist Podcast Data Science Learning Club! They appear in the order in which they joined the club, and each discuss their starting points before joining, their participation in the activities, and advice they have for new data science learners.
Podcast Audio Links: Link to podcast Episode 12 audio Podcast's RSS feed for podcast subscription apps Podcast on Stitcher Podcast on iTunes Podcast Video Playlist: Youtube playlist of interview videos More about the Data Science Learning Club: Data Science Learning Club Welcome Message
Stephanie Rivera has worked in machine learning and data science for academic research (at University of Tennessee), for the government (Department of Defense), for a large consulting firm (Booz Allen), and now for a startup (MyStrength). In the interview, she discusses her career path, her experiences with mentorship, and her role in authoring The Field Guide to Data Science and the Explore Data Science online course.
Podcast Audio Links: Link to podcast Episode 11 audio Podcast's RSS feed for podcast subscription apps Podcast on Stitcher Podcast on iTunes Podcast Video Playlist: Youtube playlist of interview videos
Trey Causey is a data scientist with a background in psychology and sociology who, like Renee, is from Virginia. He has worked as a data scientist at a range of companies from zulily to ChefSteps, and has also developed some interesting sports analytics projects, including the New York Times 4th Down bot. Trey also has advice for people wanting to start a career in data science.
Podcast Audio Links: Link to podcast Episode 10 audio
Justin Kiggins, who calls himself a "full stack neuroscientist" talks to Renee about how he started as a musician majoring in music therapy, switched to mechanical engineering, and eventually made his way via biomedical engineering and neuroscience to study auditory perception and the brains of communicating birds.
Podcast Audio Links: Link to podcast Episode 9 audio Podcast's RSS feed for podcast subscription apps Podcast on Stitcher Podcast on iTunes Podcast Video Playlist:
Renee interviews computational biologist, author, data scientist, and Michigan State PhD candidate Sebastian Raschka about how he became a data scientist, his current research, and about his book Python Machine Learning. In the audio interview, Sebastian also joins us to discuss k-fold cross-validation for our model evaluation Data Science Learning Club activity.
Podcast Audio Links: Link to podcast Episode 8 audio Podcast's RSS feed for podcast subscription apps Podcast on Stitcher Podcast on iTunes Podcast Video Playlist:
Data Scientist, Author, and manager of data science teams Enda Ridge talks to us about data governance, data provenance, reproducible analysis, work pipelines and products, and people, among other topics covered in his book "Guerrilla Analytics - A practical Approach to Working with Data: The Savvy Manager's Guide".
Podcast Audio Links: Link to podcast Episode 7 audio
In this episode, Renee interviews Bioinformatics PhD and Data Scientist Erin Shellman about her path to becoming a data scientist, including jobs at Nordstrom Innovation Lab and zymergen. Erin discusses school, job interviews, teaching, and eventually getting to do data science within her field of scientific expertise.
Podcast Audio Links: Link to podcast Episode 6 audio Podcast's RSS feed for podcast subscription apps
For anyone that hasn’t yet joined the Becoming a Data Scientist Podcast Data Science Learning Club, I thought I’d write up a summary of what we’ve been doing....
Renee Teate interviews Clare Corthell, founding partner of summer.ai and creator of the Open Source Data Science Masters curriculum, about becoming a data scientist.
Podcast Audio Links: Link to podcast Episode 5 audio Podcast's RSS feed for podcast subscription apps
In Episode 4 of the Becoming a Data Scientist Podcast, we meet Sherman Distin, owner of analytics consulting firm QueryBridge. We discuss his primarily self-taught path to learning the data science techniques he uses to find business insights in marketing data, and he also tells us what he thinks is the most important trait he looks for in data scientists.
Podcast Audio Links: Link to podcast Episode 4 audio Podcast's RSS feed for podcast subscription apps
In Episode 3 of the Becoming a Data Scientist Podcast, we meet Shlomo Argamon, who is the founding director of the Master of Data Science program at Illinois Institute of Technology. He talks to us about his path to data science, including research in robotic vision and natural language processing, we discuss the traits of a good data science student, and he gives some advice for those of us learning data science.
Note: The video is the interview only. The audio podcast has the intro, interview, and data science learning club activity explanation.
In Episode 2 of the Becoming a Data Scientist Podcast, we meet Safia Abdalla, who started programming and even exploring machine learning and natural language processing as a teenager, and is now a student at Northwestern University, a conference speaker and trainer, co-organizer of PyLadies Chicago, and a contributor to Project Jupyter.
Podcast Audio Links: Link to podcast Episode 2 audio Podcast's RSS feed for podcast subscription apps (I will distribute the feed out to iTunes and Pocket Cast ASAP. It's available on Stitcher now!)
The Becoming a Data Scientist Podcast is now available via Stitcher! Subscribe in the app, or listen online:
Note: The video is the interview only. The audio podcast has the intro, interview, and data science learning club activity explanation.
In this episode we meet Will Kurt, who talks about his path from English & Literature and Library & Information Science degrees to becoming the Lead Data Scientist at KISSmetrics. He also tells us about his probability blog, Count Bayesie, and I introduce Data Science Learning Club Activity 1. Will has some great advice for people learning data science!
Podcast Audio Links: Link to podcast Episode 1 audio Podcast's RSS feed for podcast subscription apps
Here is the first episode of the Becoming a Data Scientist Podcast, which is also available in video form!
(sorry for the poor video quality!)
In this episode, I talk a little about the podcast, I talk about my own background, and I introduce the Data Science Learning Club. Enjoy! (Note: Episode 1, the first interview episode, comes out Monday 12/21!)
Podcast Audio Links: Link to podcast Episode 0 audio Podcast's RSS feed for podcast subscription apps (I will distribute this out to sites like iTunes and Stitcher soon)
Podcast Video Playlist: Youtube playlist where I'll publish future videos More about the Data Science Learning Club:
I'm working on the last of my recording and editing for "Episode 0" of the new Becoming A Data Scientist Podcast, which I'm planning to launch tomorrow! I've already recorded the interviews for episodes 1-3, which will be airing over the next month or so - so exciting! The guests all had interesting and informative things to share, I believe you'll like it a lot.
At the end of each podcast episode, I'll be "assigning" a "Learning Activity" for the Data Science Learning Club.