Learning Resources

Over the years, I have come across multiple resources I learned things from with ease. This is a page to track those resources. Please email me if you think something belongs to this list. I will add it.


  • Julia Evans has online zines for topics ranging from SQL, Shell scripts to Linux. These are hand-drawn explanations of stuff related to a particular topic. I stumbled upon here twitter post about how SQL actually executes a query and have been a fan ever since.


  • SQL Zoo. Hands down the best place to start learning SQL. This is where I learn from and advised many mentees to learn from as well.


  • Chris Albon has a great repository of all things Python Data Science. It’s just good to just scroll through and refresh your coding memory.
  • Numpy visualized. His blog has other cool visualizations too.
  • Dan Bader’s website is a great place to learn python all around.

Data Science

  • DataCamp is good.

Machine Learning

  • Machine learning flash cards from Chris Albon is a great ML refresher. There are 300 hand-drawn cards explaining concepts related to ML. It costs $12 but are totally worth it. If that is a problem, he shares a card everyday on his twitter.
  • PCA
  • Sebastian Raschka’s book is great to get started on coding with Python. It’s easy to follow and has great code snippets. His github has good lecture notes.


  • 3blue1brown is the coolest educator I could think of. I learned so much from his videos. His series on linear algebra is my favorite.
  • Eigen Values and Eigen Vectors. I don’t think they update the website anymore. Cool visualizations nonetheless.
  • Prof. Charles Geyer (UMN Statistics) has the best slides on Intermediate Theory of Statistics I, II.


  • Rachel Thomas runs a cool blog on all things AI. I really loved her blogs on general advice in the field.