Not available in 2020/21
MA214 Half Unit
Algorithms and Data Structures
This information is for the 2020/21 session.
Teacher responsible
Prof Konrad Swanepoel
Availability
This course is available on the BSc in Management, BSc in Mathematics and Economics, BSc in Mathematics with Economics and BSc in Mathematics, Statistics and Business. This course is available as an outside option to students on other programmes where regulations permit. This course is available with permission to General Course students.
This course will also be core on the BSc in Data Science programme.
Pre-requisites
Students must have completed Mathematical Proof and Analysis (MA102).
Course content
Introduction to the fundamental principles of data structures and algorithms and their efficient implementation. Developing algorithmic thinking. Basic toolkit for the design and analysis of algorithms: Running time, Recurrence relations, Big-O notation, Correctness, Finite induction, Loop invariants. Tour of the most important data structures, fundamental algorithms, and algorithm design techniques: lists, stacks, queues, dynamic arrays, hash tables, priority queues, disjoint set unions, binary search trees, breadth-first search, depth-first search, minimum spanning tree computation, maximum flow, incremental and recursive algorithms, divide-and-conquer, greedy algorithms.
Teaching
20 hours of lectures and 10 hours of classes in the LT. 2 hours of lectures in the ST.
Formative coursework
Written answers to set problems will be expected on a weekly basis.
Indicative reading
- T H Cormen, C E Leiserson & R L Rivest, Introduction to Algorithms, MIT Press 1990 (or 2nd edn, 2001 or 3rd edn, 2009)
Assessment
Exam (80%, duration: 2 hours) in the summer exam period.
Coursework (20%) in the LT.
Important information in response to COVID-19
Please note that during 2020/21 academic year some variation to teaching and learning activities may be required to respond to changes in public health advice and/or to account for the situation of students in attendance on campus and those studying online during the early part of the academic year. For assessment, this may involve changes to mode of delivery and/or the format or weighting of assessments. Changes will only be made if required and students will be notified about any changes to teaching or assessment plans at the earliest opportunity.
Key facts
Department: Mathematics
Total students 2019/20: Unavailable
Average class size 2019/20: Unavailable
Capped 2019/20: No
Value: Half Unit
Personal development skills
- Self-management
- Problem solving
- Application of information skills
- Communication
- Application of numeracy skills
- Specialist skills
