Advanced Algorithms and Data Structures (AADS)
Course content
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 specialised elective courses.
MSc Programme in Computer Science
MSc Programme in Computer Science (part time)
MSc Programme in Computer Science with a minor subject
MSc Programme in Bioinformatics
Knowledge of
- Graph algorithms such as max flow.
- Data structures such as van Emde Boas Trees.
- NP-completeness.
- Exponential and parameterised algorithms for NP-hard problems.
- Approximation algorithms.
- Randomised algorithms.
- Computational geometry.
- Linear programming and optimisation.
Skills to
- Analyse algorithms with respect to correctness and efficiency.
- Explain and use basic randomised algorithms.
- Recognise 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
- Analyse a computational problem in order to find an appropriate algorithmic approach to solve it.
A mix of lectures and exercises.
See Absalon when the course is set up.
It is assumed that the students are familiar with basic
algorithms (sorting, selection, minimum spanning trees, shortest
paths) and data structures (lists, stacks, binary trees, search
trees, heaps).
Academic qualifications equivalent to a BSc degree is
recommended.
As
an exchange, guest and credit student - click here!
Continuing Education - click here!
PhD’s can register for MSc-course by following the same procedure as credit-students, see link above.
- ECTS
- 7,5 ECTS
- Type of assessment
-
Oral examination, 30 minutes
- Type of assessment details
- Oral examination in course curriculum with 30 minutes preparation
- Aid
- All aids allowed
- Marking scale
- 7-point grading scale
- Censorship form
- External censorship
Criteria for exam assessment
See learning outcome.
Single subject courses (day)
- Category
- Hours
- Lectures
- 36
- Preparation
- 85
- Theory exercises
- 84
- Exam
- 1
- English
- 206
Kursusinformation
- Language
- English
- Course number
- NDAA09023U
- ECTS
- 7,5 ECTS
- Programme level
- Full Degree Master
- Duration
-
1 block
- Placement
- Block 2
- Schedulegroup
-
C
- Capacity
- No limit
The number of seats may be reduced in the late registration period - Studyboard
- Study Board of Mathematics and Computer Science
Contracting department
- Department of Computer Science
Contracting faculty
- Faculty of Science
Course Coordinator
- Christian Wulff-Nilsen (7-6e72726f72727d43676c316e7831676e)
Teacher
Mikkel Abrahamsen, Jacob Holm, Danupon Nanongkai, Pawel Winter, Christian Wulff-Nilsen
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Courseinformation of students