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252-0209-00L 8 Credits BSC , MSC D-INFK , D-MATH

Algorithms, Probability, and Computing

Lecturers & Examiners: Prof. Dr. Bernd Gärtner, Prof. Dr. Karl Bringmann, Prof. Dr. Rasmus Kyng, Dr. Maximilian Probst

VVZ CR 2.91

Last Updated: 2026-06-03 00:07:49

Abstract

Advanced design and analysis methods for algorithms and data structures: Random(ized) Search Trees, Point Location, Minimum Cut, Linear Programming, Randomized Algebraic Algorithms (matchings), Probabilistically Checkable Proofs (introduction).

Objective

Studying and understanding of fundamental advanced concepts in algorithms, data structures and complexity theory.

Resources

Lecture Notes

Will be handed out.

Literature

Introduction to Algorithms by T. H. Cormen, C. E. Leiserson, R. L. Rivest; Randomized Algorithms by R. Motwani und P. Raghavan; Computational Geometry - Algorithms and Applications by M. de Berg, M. van Kreveld, M. Overmars, O. Schwarzkopf.

General Information

Language: English
Levels: BSC , MSC
Frequency: Yearly recurring

Examination

Type: session examination
Mode: written 180 minutes
Aids: Keine Hilfsmittel erlaubt.

There will be an optional written midterm exam and a written final exam. Script or any other supplementary material for either exam is not permitted. Furthermore, we will hand out two special assignments (compulsory continuous performance assessment) whose solution (typeset in LaTeX) is due two weeks later and will be graded.The final grade is 20% midterm exam + 20% special assignments + 60% final examORif the result of the midterm exam does not improve the final grade or has not been sitted:20% special assignments + 80% final exam

Course Components

Type	Title	Time & Place	Hours
lecture	Algorithms, Probability, and Computing	No time listed	4 h weekly
exercise	Algorithms, Probability, and Computing	No time listed	2 h weekly
independent project	Algorithms, Probability, and Computing Project Work, no fixed presence required.	No time listed	1 h weekly

Offered In

Computational Science and Engineering Bachelor
- Electives (In the ‘electives’ subcategory, at least two course units must be successfully completed.)
Computer Science Bachelor
- Core Courses
  - Major: Theoretical Computer Science
Mathematics Bachelor
- Core Courses and Elective Courses
  - Core Courses
    - Core Courses: Applied Mathematics and Further Appl.-Oriented Fields (¬)
Computational Science and Engineering Master
- Electives (In the ‘electives’ subcategory, at least two course units must be successfully completed. All courses listed as core courses (not electives) for one of the following ETH MSc programmes, MSc Statistics, MSc Physics, MSc Computer Science, MSc (Applied) Mathematics, MSc Neural Systems and Computation, MSc Robotics, Systems, and Control, MSc Data Science, MSc Electrical Engineering and Information Technology, can be taken as an elective course in the MSc CSE without prior permission.)