NDAA09023U Advanced Algorithms and Data Structures (AADS)
MSc Programme in Computer Science
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.
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.
See Absalon when the course is set up.
- Category
- Hours
- Exam
- 2
- Lectures
- 36
- Preparation
- 84
- Theory exercises
- 84
- Total
- 206
As
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Continuing Education - click here!
- Credit
- 7,5 ECTS
- Type of assessment
- Oral examination, 30 minutesOral exam with preparation (30 minutes) in course curriculum.
- Exam registration requirements
In order to qualify for the exam the student must complete 2 mandatory exercises.
- Aid
- All aids allowed
- Marking scale
- 7-point grading scale
- Censorship form
- External censorship
- Re-exam
If student is not qualified then qualification can be achieved by hand-in and approval of equivalent exercises.
Re-exam same as ordinary exam.
Criteria for exam assesment
See learning outcome.
Course information
- Language
- English
- Course code
- NDAA09023U
- Credit
- 7,5 ECTS
- Level
- Full Degree Master
- Duration
- 1 block
- Placement
- Block 1
- Schedule
- C
- Course capacity
- No limit
- Continuing and further education
- Study board
- Study Board of Mathematics and Computer Science
Contracting department
- Department of Computer Science
Course responsibles
- Mikkel Thorup (7-7f867a8184878252767b407d8740767d)