Courses

Below is a list of graduate level courses I have taken.

University of Southern California

1. DSO 699- Bandit Algorithms and Reinforcement Learning- Spring’25
2. CSCI 678- Theoretical Machine Learning- Fall’24
3. EE 550- Data Networks- Spring’24
4. ISE 633- Large Scale Optimization and Machine Learning- Spring’24
5. EE 649- Stochastic Network Optimization and Adaptive Learning- Fall’23
6. EE 503-Probability for Electrical and. Computer Engineers- Fall’22
7. EE 510-Linear Algebra for Engineering- Fall’22
8. EE 562-Random Processes in Engineering- Spring’23
9. Math 425b-Fundamental Concepts of Analysis- Spring’23

Online Courses

1. Machine Learning - Stanford University, Coursera, Certificate
2. Neural Networks and Deep Learning - Stanford University, Coursera Certificate
3. Improving Deep Neural Networks - Stanford University, Coursera, Certificate
4. Sequence models - Stanford University, Coursera, Certificate
5. Probabilistic Graphical Models 1: Representation - Stanford University, Coursera, Certificate
6. EE263 Introduction to Linear Dynamical Systems - Stanford University
7. EE364A Convex Optimization 1 - Stanford University
8. Classical Mechanics - Stanford University
9. Introduction to Complex Analysis - Wesleyan University, Coursera, Certificate
10. Bayesian Methods for Machine Learning (with Honours) - Higher School of Economics, Coursera, Certiificate
11. Macroeconomics - Khan Academy