Becoming A Data Scientist Podcast Episode 0: Me!

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:
Blog post about Data Science Learning Club
Learning Club Activity 0: Set up your development environment
Data Science Learning Club Meet & Greet

Here are the links with more info of things I reference in the video:

turtle logo programming language

carmen sandiego

C programming language

JMU Integrated Science and Technology (ISAT)

Visual Basic/VB.NET/ASP.NET
MS Access

Rosetta Stone

Oracle Data Warehouse
IBM Cognos

CGEP UVA Systems Engineering
Systems Engineering
Linear Algebra at Khan Academy
Stochastic Simulation
Cognitive Systems Engineering
Principles of Data Visualization for Exploratory Data Analysis
Machine Learning
Naive Bayes
Pattern Recognition and Machine Learning (class textbook)

Summer of Data Science
API and Market Basket Analysis
Docker and Jupyter
Doing Data Science by Cathy O’Neill and Rachel Schutt
O’Reilly Data Science Books
(I’ll post more specific books later)


  1. Yoly
    Dec 15, 2015

    Great first episode Renee.

    You mentioned that for one of your final projects you used a random forest to predict which non-donors would become a first time donor in a given year. I’m curious as to what you used as features for this model, or at least, which data from the members did you have available.

    Looking forward to the next episode!

    • Renee
      Dec 15, 2015

      Hi Yoly, that’s why I didn’t jump to publish… I need to make sure my features weren’t allowing any “data leakage” or anything. I remember including preferred college, preferred class year (usually their undergrad degree year), years since added to system, years since address updated (if we didn’t have an address for 10 years, then suddenly have it, they may become a donor), age (which isn’t always derivable from class year), and a few other things… When I do revisit it, I’ll blog about it!

      Oh actually, I did blog about the first one… haha here’s the link :) Just keep in mind I did this for a hurry for a class project:

      And here’s the data visualization for exploratory data analysis project I mentioned:


    • Renee
      Dec 15, 2015

      Oh, and thanks so much for the positive feedback!

    • Yoly
      Dec 17, 2015

      Thank you for sharing.

      Very detailed document, I loved it. For my Capstone Project for the Coursera Data Science Specialization I was limited to 5 pages max for the write-up so I couldn’t go into too much detail which sucked.

      If this is what you can do “in a hurry” I can only imagine what you can do if you don’t rush it, hahaha. Very cool project. Congrats on the feedback by your professor.

    • Renee
      Dec 17, 2015

      haha thanks for the positive feedback – glad you liked it!

  2. Renee
    Jan 19, 2016

    Somebody flagged this video as inappropriate and YouTube said they confirmed it and it got taken down! I can’t figure out which Community Guideline it could possibly have violated…. does anyone have any ideas?? I’m appealing it, of course.

    I can’t even tweet about it right now because Twitter is down! LOL what happened to the internet?

  3. shacharm
    Jul 6, 2016

    Hi – you mentioned an ML course in odu?
    Would you be able to point to that course?