Courses

From undergrades to PhDs, the EPFL has plenty of courses to offer..

Bachelor

• CIVIL-226 – Introduction to machine learning for engineers
• CS-233(a) – Introduction to machine learning (BA3)
• CS-233(b) – Introduction to machine learning (BA4)
• CS-330 – Artificial intelligenceCS-330 – Artificial Intelligence
• BIO-322 – Introduction to machine learning for bioengineers
• MATH-352 – Causal thinking
• ME-390 – Foundations of Artificial Intelligence

Master

• CIVIL-459 – Deep learning for autonomous vehicles
• CS-401 – Applied Data Analysis
• CS-430 – Intelligent Agents
• CS-433 – Machine Learning
• CS-439 – Optimization for Machine Learning
• CS-449 – Systems for data science
• CS-526 – Learning theory
• CS-503 – Visual intelligence : machines and minds
• COM-406 – Foundations of Data Science
• DH-406 – Machine Learning for the Digital Humanities
• EE-411 – Fundamentals of inference and learning
• EE-452 – Network machine learning
• EE-556 – Mathematics of data
• EE-559 – Deep Learning
• EE-566 – Adaptation and learning
  • EE-568 – Reinforcement learning
• ENV-540 – Image processing for Earth observation
• MATH-403 – Low-rank approximation techniques
• MATH-412 – Statistical machine learning
• MATH-520 – Mathematics of machine learning
• MGT-418 – Convex optimization
• MICRO-401 – Machine Learning Programming
• MICRO-455 – Applied Machine Learning
• MICRO-570 – Advanced Machine Learning

Doctoral Courses and continued education

• CS-612 – Topics in Natural Language Processing
• CS-723 – Topics in Machine Learning Systems
• EE-608 – Deep Learning For Natural Language Processing
• EE-613 – Machine learning for engineers
• EE-618 – Theory and Methods for Reinforcement Learning
• EE-735 – Online learning in games
• ENG-369 – Dynamic programming and optimal control
• ENG-639 – Dynamic programming and optimal control
• ENG-704 – EECS Seminar: Advanced Topics in Machine Learning
• EPFL Extension School – Applied Data Science: Machine Learning