Courses

Mathematical Foundations:

• Real Analysis, Functional Analysis

• High-dimensional Probability 

• The Interplay between Convex Optimization and Geometry 

• Continuous Algorithms: Optimization and Sampling

• Matrix Calculus for Machine Learning and Beyond

Machine Learning:

• Foundations of Deep Learning (U. Maryland)  (Videos)

• Foundations of Reinforcement Learning (Princeton) (Videos)

• TinyML and Efficient Deep Learning Computing (MIT) (Videos)

• Advanced NLP (CMU) (Videos)

Quantum Computing:

• Introduction to Quantum Computing (Columbia) 

• Frontiers of Quantum Complexity and Cryptography (Columbia)

• Quantum Computing (CalTech) (Videos)

Useful Links

1. Francis Bach's Machine Learning Research Blog

2. Greg Yang's website on Neural Tangent Kernel

3. QuTech Quantum Courses

4. QuantumGrad