Teaching


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

Master-Level Courses

Fall semester

Discrete Math (MTAT.05.008)

  • compulsory for 1st year Computer Science master students
  • algorithm-focused 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)
    • No-Proof Branch: the basic stuff for non-theorists ("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)
  • proof-based course based on Blum-Hopcroft-Kannan

CooCoo: Combinatorial and Convex Optimization (MTAT.05.120)

  • 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 primal-dual 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

Infrequently

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, ...

PhD-Level Courses

These courses are organized with more student participation than lower level courses, e.g., independent textbook reading.

Fall semester

Methods in Theoretical Computer Science I-IV (MTAT.05.121)

  • four independent(!) courses on PhD level
  • backbone of theoretical computer science research:
    1. Combinatorics in computer science
    2. Advanced randomness and probabilistic analysis
    3. Quantum computation and information
    4. Advanced complexity

Rules

How oral exams are conducted