Official course description:
Basic info last published 26/02-19

### Algorithm Design, MSc CS

##### Course info
Language:
English
ECTS points:
7.5
Course code:
KSALDES1KU
Offered to guest students:
-
Offered to exchange students:
Offered as a single subject:
-
##### Programme
Level:
MSc. Master
Programme:
M.Sc. in IT, Computer Science
Semester
Efterår 2018
Start
27 August 2018
End
28 December 2018
##### Abstract

This course is an advanced course on algorithms which builds on top of an introductory course on algorithms and data structures. The course focuses on advanced techniques for identifying and solving computationally hard problems and on how to adapt such techniques to real-world scenarios.

##### Description

This course introduces students to techniques for solving complex programming tasks arising in modern IT systems. The student taking this course will be able to quickly identify and solve a certain class of problems that can arise among the tasks that a skilled programmer must solve.

Focus in the course is on algorithm design and identification of computationally hard problems. The course contains both theoretical and analysis and implementation exercises.

Contents of lectures includes: Formulating an algorithmic problem, greedy algorithms, graph algorithms, divide and conquer, dynamic programming, network flow, reductions.

##### Formal prerequisites
Before the course, the student should be able to: Perform basic analysis of algorithm correctness and complexity, using invariants and big-O notation. Use basic algorithms and data structures when programming (e.g., lists, queues, stacks, search trees, hashing, sorting algorithms, and basic graph algorithms). This can be achieved, for example, by taking the courses "Foundations of Computing - Algorithms and Data Structures" or "Algorithms and Data Structures" (BADS).
##### Intended learning outcomes

After the course, the student should be able to:

• Solve a wide range of real-life programming problems in a scalable way by employing algorithmic design techniques and tools.
• Identify and formulate precisely (if possible) the algorithmic problem underlying in a given programming task.
• Apply the following algorithmic techniques when solving a problem: Greedy, divide and conquer, dynamic programming, reduction to network flow.
• Look up suitable NP hardness results in a compendium, and perform simple reductions from such problems to establish NP hardness.
##### Ordinary exam
Exam type:
X: Special exam type, external (7-trinsskala)
Exam description:
4 hours written exam on premises with all written aids (course book, own notes, printouts of slides, etc.). No use of electronic communication tools such as PC, laptop, tablet or e-reader with internet or other network connection or mobile phone. Please notice that the exam takes place at ITU. Only use of pen is allowed for the final exam hand-in. Form of re-exam is the same as the ordinairy exam.