MA407 Half Unit
Algorithms and Computation
This information is for the 2020/21 session.
Teacher responsible
Prof Konrad Swanepoel and Prof Julia Boettcher
Availability
This course is available on the MSc in Applicable Mathematics, MSc in Data Science, MSc in Operations Research & Analytics, MSc in Statistics, MSc in Statistics (Financial Statistics), MSc in Statistics (Financial Statistics) (LSE and Fudan), MSc in Statistics (Financial Statistics) (Research) and MSc in Statistics (Research). This course is available with permission as an outside option to students on other programmes where regulations permit.
The course is compulsory for students on the MSc Applicable Mathematics who are not taking MA421 Advanced Algorithms; it is optional for students on the MSc Applicable Mathematics who take MA421 Advanced Algorithms.
Pre-requisites
Good general knowledge of mathematics, including familiarity with abstract concepts. A willingness to cope with technical details of computer usage, and with a rapid introduction to programming.
Course content
Introduction to programming in Java. Introduction to the theory of algorithms: running time and correctness of an algorithm. Recursion. Data structures: arrays, linked lists, stacks, queues, binary search trees. Sorting algorithms. Greedy algorithms. Dynamic programming. Inheritance and Generics in Java.
Teaching
This course is delivered through a combination of seminars and lectures totalling a minimum of 30 hours across Michaelmas Term. There are also optional computer help sessions for this course. Before the start of Michaelmas Term there will be 6 hours of pre-sessional programming tutorials. This year, some or all of this teaching will be delivered through a combination of virtual classes and lectures delivered as online videos.
Formative coursework
Weekly exercises are set and marked. Many of these will require implementation of programming exercises in Java.
Indicative reading
R Sedgewick, K Wayne, Introduction to programming in Java.
T H Cormen, C E Leiserson, R L Rivest and C Stein, Introduction to Algorithms.
Assessment
Exam (50%, duration: 2 hours) in the summer exam period.
Coursework (25%) in the LT.
Coursework (15%) in the MT.
Continuous assessment (10%).
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: 49
Average class size 2019/20: 48
Controlled access 2019/20: No
Value: Half Unit
Personal development skills
- Self-management
- Problem solving
- Application of information skills
- Communication
- Application of numeracy skills
- Specialist skills
