This spring, I’m teaching a graduate-level special topics course called “Mathematics of Data Science” at the Ohio State University. This will be a research-oriented class, and in lecture, I plan to cover some of the important ideas from convex optimization, probability, dimensionality reduction, clustering, and sparsity.

Click here for a draft of my lecture notes.

The current draft consists of a chapter on convex optimization. I will update the above link periodically. Feel free to comment below.

**UPDATE #1:** Lightly edited Chapter 1 and added a chapter on probability.

**UPDATE #2:** Lightly edited Chapter 2 and added a section on PCA.

**UPDATE #3:** Added a section on random projection.

**UPDATE #4:** Lightly edited Chapter 3. The semester is over, so I don’t plan to update these notes again until I teach a complementary special topics course next year.