twentytwentyone domain was triggered too early. This is usually an indicator for some code in the plugin or theme running too early. Translations should be loaded at the init action or later. Please see Debugging in WordPress for more information. (This message was added in version 6.7.0.) in /home1/moderna7/public_html/wp-includes/functions.php on line 6170Documenting my path from "SQL Data Analyst pursuing an Engineering Master's Degree" to "Data Scientist"
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.
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!
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.
As data scientists, we are aware that bias exists in the world. We read up on stories about how cognitive biases can affect decision-making. We know that, for instance, a resume with a white-sounding name will receive a different response than the same resume with a black-sounding name, and that writers of performance reviews use different language to describe contributions by women and men in the workplace. We read stories in the news about ageism in healthcare and racism in mortgage lending.
Data scientists are problem solvers at heart, and we love our data and our algorithms that sometimes seem to work like magic, so we may be inclined to try to solve these problems stemming from human bias by turning the decisions over to machines. Most people seem to believe that machines are less biased and more pure in their decision-making – that the data tells the truth, that the machines won’t discriminate.
I have been thinking about doing a “Becoming a Data Scientist” podcast for a long time, at least since April. The podcast would include interviews focused on how people working in various data-science-related jobs got to where they are today (how did they “become a data scientist”?). I’m getting closer to taking the dive and getting it started.
I had an idea today that would take it a step further. Imagine how book clubs work where you pick a book, go off and read it, then gather occasionally to discuss and record your thoughts. Except instead of a book club, it’s a data science learning club!
