The Seminar
Algorithms & Theory Seminar (MTAT.05.116)
 every semester
 present an algorithm and its analysis, or
 present a theorem and its proof.
 compulsory for Master's and PhD students specializing in A&T
MasterLevel Courses
Fall semester
Discrete Math (MTAT.05.008)
 compulsory for 1st year Computer Science master students
 algorithmfocused theory course
 students can take choose a "Branch" in line with their interests and aptitudes:
 Proof Branch: The foundations you need everywhere in Theoretical Computer Science (discrete probability, information theory, boolean functions and Fourier transform, quantum computation)
 NoProof Branch: the basic stuff for nontheorists ("What is a graph?")
Complexity Theory (MTAT.07.004)
 introductory course
 taught by Dominique from Crypto
Spring semester
Foods: Foundations of Data Science (MTAT.05.123)
 every 2nd year (alternates with CooCoo, MTAT.05.120)
 proofbased course based on BlumHopcroftKannan
 every 2nd year (alternates with Foods MTAT.05.123)
 introduction to the problems and techniques
Advanced Methods in Algorithms (MTAT.03.286)
 every 2nd year (alternates with Introduction to Coding Theory MTAT.05.082)
 from Fast Fourier Transform to primaldual algorithms
 taught by Vitaly from Coding Theory
Introduction to Coding Theory (MTAT.05.082)
 every 2nd year (alternates with Advanced Methods in Algorithms MTAT.03.286)
 the name says it all...
 taught by Vitaly from Coding Theory
Problem Solving (MTAT.05.118)
 solving hard problems in groups
Randomized Algorithms (MTAT.05.117)
 Builds on the Proof Branch of MTAT.05.008
 randomized algorithms and their analysis
 with a modern slant: sublinear time, data streams, ...
These courses are organized with more student participation than lower level courses, e.g., independent textbook reading.
Methods in Theoretical Computer Science IIV (MTAT.05.121)
 four independent(!) courses on PhD level
 backbone of theoretical computer science research:
 Combinatorics in computer science
 Advanced randomness and probabilistic analysis
 Quantum computation and information
 Advanced complexity
Rules
