Course

ENG-466: Distributed intelligent systems

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CS-450: Algorithms II

A first graduate course in algorithms, this course assumes minimal background, but moves rapidly. The objective is to learn the main techniques of algorithm analysis and design, while building a reper

COM-406: Foundations of Data Science

We discuss a set of topics that are important for the understanding of modern data science but that are typically not taught in an introductory ML course. In particular we discuss fundamental ideas an

CIVIL-226: Introduction to machine learning for engineers

Machine learning is a sub-field of Artificial Intelligence that allows computers to learn from data, identify patterns and make predictions. As a fundamental building block of the Computational Thinki

MATH-600: Optimization and simulation

Master state-of-the art methods in optimization with heuristics and simulation. Work involves:

reading the material beforehand
class hours to discuss the material and solve problems
homework

CS-452: Foundations of software

The course introduces the foundations on which programs and programming languages are built. It introduces syntax, types and semantics as building blocks that together define the properties of a progr

MATH-232: Probability and statistics (for IC)

A basic course in probability and statistics

CS-420: Advanced compiler construction

Students learn several implementation techniques for modern functional and object-oriented programming languages. They put some of them into practice by developing key parts of a compiler and run time

ENG-410: Energy supply, economics and transition

This course examines energy systems from various angles: available resources, how they can be combined or substituted, their private and social costs, whether they can meet the energy demand, and how

ENG-270: Computational methods and tools

This course prepares students to use modern computational methods and tools for solving problems in engineering and science.

ENG-366: Signals, instruments and systems

The goal of this course is to transmit knowledge in sensing, computing, communicating, and actuating for programmable field instruments and, more generally, embedded systems. The student will be able