Algorithm Design, MSc CS
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.
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 prerequisitesBefore 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.
Teaching consists of a mix of lectures and exercises.
Mandatory activities12 mandatory programming assignments must be approved to qualify for the exam.
The student will receive the grade NA (not approved) at the ordinary exam, if the mandatory activities are not approved and the student will use an exam attempt.
The course literature is published in the course page in LearnIT.
Student Activity BudgetEstimated distribution of learning activities for the typical student
- Preparation for lectures and exercises: 25%
- Lectures: 15%
- Exercises: 25%
- Assignments: 25%
- Exam with preparation: 10%
Ordinary examExam type:
A: Written exam on premises, External (7-point scale)
A33: Written exam on premises on paper with restrictions
Written and printed books and notes