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)
