I’m teaching an RL short course, based on materials in Sutton and Barto (2018), Puterman (2014), DeepMind & UCL RL lecture series and some research papers.

• Lecture 1 Foundations of RL
• Lecture 2 Planning & Learning
• Lecture 3 Q-Learning and Beyond
• Lecture 4 Policy- and Model-based Learning
• Lecture 5 Offline RL

Teaching @ LSE

• MT 2019 – MT 2021: Managing and Visualising Data (ST445)
• LT 2022: Reinforcement Learning (ST455)
• MT 2020 – LT 2021: Probability, Distribution Theory and Inference (ST202)
• LT 2021 – LT 2022: Foundations of Machine Learning (ST510)

TA @ NCSU

• Fall 2014: Experimental Statistics for Biological Science (ST511)
• Spring 2015: Experimental Statistics for Biological Science (ST511)
• Fall 2018: Experimental Statistics for Engineers (ST515)
• Spring 2019: Experimental Statistics for Engineers (ST515)

TA @ ZJU

• Spring 2014: Financial Risk Management