Data Structures and Algorithms 2, Online teaching

A student who has completed the course with a least the grade "good" is expected to

• be able to analyse formally the asymptotic complexity of basic (including recursive) algorithms
• be able to apply and analyse common algorithm design methods in solving various problems
  
• be able implement intermediate-level algorithms efficiently in C, C++, Java or Python.
  

The course introduces typical algorithmic problem solving methods (greedy algorithms, divide & conquer, dynamic programming, flow graphs) and string algorithms. The course emphasizes algorithm implementation (= programming) over theory.

The course contains two mandatory elements:
1) Completing a sufficient amount of automatically graded weekly programming tasks and theory questions.
2) Passing a final electronic exam, which contains both programming tasks and theory questions (similar to exercises).

The course in addition offers weekly lectures / Q&A sessions that are recorded and made available for later viewing. Participation to these is not mandatory but may be encouraged by awarding extra points that count towards the course grade.

Prerequisites

The course requires reasonable programming skills. You are allowed to use any of the following programming languages during the course: C, C++, Java or Python.

Recommended Prerequisites

• Data Structures, TIETA6, 10 cr
• Data Structures and Algorithms 1, COMP.CS.300, 5 cr
• Mathematics for Algorithms 1, MAT-02651, 5 cr
• Basic concepts of Mathematics, MTTMY1, 5 cr

Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest and Clifford Stein: Introduction to Algorithms

Lecture recordings and written material will be provided in WETO.

General scale, 0-5