My Curriculum

My background coming in:

I have a B.Eng. from Cooper Union so I had a strong knowledge of Calculus (up to analysis), probability (up to a graduate level course in stochastic processes with my Masters thesis being on the application of Monte Carlo methods), and Linear Algebra

Math

Linear Algebra 

Courses: 

MIT OCW

This is actually the best online course available as Professor Strang's lectures are just things of beauty and elegance. The provided homeworks and exams are a bit too easy, but the thoroughness of the lectures more than makes up for it.

Books:

Linear Algebra Done Right

Convex Optimization

Stanford

Definitely the most challenging course I did, learned a significant amount form it though.

Books:

Included (for free) with the above lectures

Programming

I had a decently strong knowledge of C, Python, SQL, and R coming in

Courses

Algorithms: Design and Analysis part 1 part 2

Heterogeneous Parallel Programming

Discrete Optimization (In progress)




Books

Introduction to Algorithms
CUDA By Example
Integer and Combinatorial Optimization (In progress, this book is not easy)

Data Science Basics

JHU Data Science Specialization (Completed all but capstone, chose to skip this capstone since NLP doesn't really interest me)

Data Mining
Pattern Discovery in Data Mining
Text Retrieval and Search Engines (In progress)
Process Mining (In progress)
Mining Massive Datasets

Books:
Mining of Massive Datasets

Machine Learning

Machine Learning
Statistical Learning
The Analytics Edge (In progress)

Books

Introduction to Statistical Learning
Elements of Statistical Learning  (In progress)

Papers

Memory Networks

AI

General Game Playing (In progress)