PHYS-467: Machine learning for physicistsMachine learning and data analysis are becoming increasingly central in sciences including physics. In this course, fundamental principles and methods of machine learning will be introduced and practised. ...
ENG-704: EECS Seminar: Advanced Topics in Machine LearningStudents learn about advanced topics in machine learning, artificial intelligence, optimization, and data science. Students also learn to interact with scientific work, analyze and understand strengths and weaknesses of scientific arguments of both theoret ...
ENV-540: Image processing for Earth observationThis course covers optical remote sensing from satellites and airborne platforms. The different systems are presented. The students will acquire skills in image processing and machine/deep learning to extract end-products from the images such as land cover ...
EE-805: Fundamentals of Image AnalysisThis summer school is an hands-on introduction on the fundamentals of image analysis for scientists. A series of lectures provide students with the key concepts in the field, and are followed by practical sessions with popular software on the participants' ...
EE-735: Online learning in gamesThis course provides an overview of recent developments in online learning, game theory, and variational inequalities and their point of intersection with a focus on algorithmic development. The primary approach is to lay out the different problem classes ...
MGT-424: Machine learning methods in econometricsThis course aims to provide graduate students a grounding in the methods, theory, mathematics and algorithms needed to apply machine learning techniques to in business analytics domain. The course covers topics from machine learning, classical statistics, ...
CS-430: Intelligent agentsSoftware agents are widely used to control physical, economic and financial processes. The course presents practical methods for implementing software agents and multi-agent systems, supported by programming exercises, and the theoretical underpinnings inc ...
FIN-616: Financial Econometrics II (2020 -2024)This course has 3 parts
- We understand how to use moment based estimations to obtain the parameters for explicit or implicit models.
- We learn how to estimate latent parameters in a time series context with the Kalman filter.
- Machine learning tools bel ...
CS-456: Deep reinforcement learningThis course provides an overview and introduces modern methods for reinforcement learning (RL.) The course starts with the fundamentals of RL, such as Q-learning, and delves into commonly used approaches, like PPO and DQN. The course will introduce student ...
FIN-418: Machine learning for financeThis course is introduces machine learning techniques for financial applications in algorithmic trading, derivatives pricing, model calibration, hedging, and risk management. The course format is hands on coding sessions in Python (Keras, Tensorflow, and S ...
