Advanced Algorithms and Data Structures (AADS)

Course content

Algorithms is about finding scalable solutions to computational problems, and the reliance is only increasing as we enter the world of Big Data. We want algorithms that solve problems efficiently relative to the input size. Exponential time is hopeless. We generally want polynomial time, and for large problems we need linear time. Sometimes we employ data structures that represent the input so that queries about it can be answered very efficiently. In this mandatory course, we will study the list of algorithmic topics below. Some of these topics are covered in more depth in more specialized elective courses.

Education

MSc Programme in Computer Science

Learning outcome

Knowledge of:

  • Graph algorithms such as max flow
  • NP-completeness
  • Approximation algorithms
  • Randomized algorithms
  • Computational geometry
  • Linear programming and optimization

 

Skills to:

  • Analyze algorithms with respect to correctness and efficiency.
  • Explain and use basic randomized algorithms.
  • Recognize NP-hard problems and address them, e.g., using approximation algorithms.
  • Explain and use algorithms for different abstract domains such as graphs and geometry.
  • Formulate real-life problems as algorithmic problems and solve them.

 

Competences to:

  • Analyze a computational problem in order to find an appropriate algorithmic approach to solve it.

A mix of lectures and exercises.

See Absalon when the course is set up.

It is assumed that the students are familiar with basic algorithms (sorting, selection, minimum spanning trees, shortest paths) and data structures (lists, stacks, binary trees, search trees, heaps).

ECTS
7,5 ECTS
Type of assessment
Oral examination, 30 minutes
Oral exam with preparation (30 minutes) in course curriculum.
Aid
All aids allowed
Marking scale
7-point grading scale
Censorship form
External censorship
Criteria for exam assessment

See learning outcome.

Single subject courses (day)

  • Category
  • Hours
  • Lectures
  • 36
  • Theory exercises
  • 84
  • Preparation
  • 84
  • Exam
  • 2
  • English
  • 206