Learning Resources for DATA 1010

Primary resources

  • edX. We have deployed the book for this class as a private edX course. Allow plenty of time to work through the material and think carefully about the problems.

  • Pre-class videos. Watch an expository video on the material for each day on YouTube (linked from the main course page). These videos are deliberately fast-paced so you can use them for a high-level summary or review, but for that reason you should expect to make generous use of the pause button. Be prepared to watch a video multiple times to reinforce your learning.

  • Class time. Come to class prepared to engage, ask questions, and learn as much as possible.

  • Homework. Complete each homework question with the goal of understanding it thoroughly. Reflect on the principles you used to solve the question, how you recognized which principles would be useful, and the bigger picture the problem is trying to illuminate. If you sense that there are some things you aren't completely grasping, please attend office hours or the MRC (see last two items below) for more conversation. When the solutions are posted after the deadline, read them to learn details you might have missed when you solved the problem yourself.

  • Instructor and TA office hours. Students often find that office hours are extremely helpful. You do not have to have any pressing needs to attend office hours: you are welcome to come to chat about the course or go over problems you feel you already mostly understand or whatever. If you feel you have some kind of hangup about coming to office hours, you should come once merely for the sake of clearing that hurdle.

  • Piazza. Ask questions (including anonymously) on the course Piazza page.

  • Your fellow students. Collaboration on solving homework problems is encouraged (though the final write-up must still be your own!), because you can learn a lot from working through problems with one another.

Secondary resources

  • Cheat sheet. A list of bullets points with takeaways from each lesson is available here. This document is helpful for refreshing your memory on the most important concepts before you tackle the homework, and it's also helpful for identifying examinable content.

  • Other Books. The edX content is not designed to be encyclopedic. It is intended to be concise and approachable, with the goal of cultivating a robust understanding of the basic ideas. For a more comprehensive of advanced treatment, see Sheldon Ross's A First Course in Probability, Larry Wasserman's All of Statistics, and Pattern Recognition and Machine Learning by Christopher Bishop. For review of linear algebra and numerical computation, see the Deep Learning book by Goodfellow, Bengio, and Courville.

  • 3Blue1Brown videos. 3Blue1Brown is the YouTube moniker of a person who has made some conceptually lucid and graphically stunning explanatory math videos, including a whole series on linear algebra. These videos are quite short and will provide you with some really valuable geometric intuition. These mental models are much more readily conveyed with the kinds of rich animation tools 3b1b is using. Highly recommended for the covered topics (just the vector stuff)