Algorithms and Data Structures

The course is about problem solving using algorithmic thinking.

Techniques and algorithms:

• Recursion
• Sorting
• Searching
• Hashing
• Graph algorithms

Data structures:

• Tables/arrays
• Lists
• Queues
• Stacks
• Trees
• Graphs

Complexity theory:

• Complexity and Big O notation
• Time- and memory use

Knowledge - candidate:

• Is familiar with, can explain and apply a set of standard algorithms, including sorting, searching and graph algorithms.
• Can describe and explain different data structures (arrays/tables, linked lists, queues, stacks, trees and graphs).
• Understands recursive thinking/method for problem solving and programming.
• Can compare algorithm complexity.
• Can describe NP-completeness.

Skills - candidate:

• Can apply a set of known algorithms for effectively solve practical programming problems.
• Can handle advanced data structures (with emphasis on trees and graphs)

General competence - candidate:

• Can combine standard algorithms into larger programs.
• Is aware of the connection between complexity and execution time for programs

Lectures, exercises, mentoring.