MA421 Half Unit
Advanced Algorithms
This information is for the 2020/21 session.
Teacher responsible
Dr Tugkan Batu and Prof Gregory Sorkin
Availability
This course is available on the MSc in Applicable Mathematics and MSc in Operations Research & Analytics. This course is available as an outside option to students on other programmes where regulations permit.
Pre-requisites
Students must have completed Algorithms and Computation (MA407) or have taken an equivalent course to provide a basic knowledge in analysis of algorithms: running time and correctness of an algorithm, and basic knowledge of computer programming (preferably in Java). Students should be comfortable with proofs and proof techniques used in pure mathematics.
Course content
Introduction to NP-Completeness, followed by Approximation Algorithms, Randomised Algorithms, and other topics such as some of Average-Case Analysis, Streaming Algorithms, Exponential-Time Algorithms, and Numerical Algorithms.
Teaching
This course is delivered through a combination of classes and lectures totalling a minimum of 30 hours across Lent Term. 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. Some of these will include programming exercises in Java.
Indicative reading
Cormen, Leiserson, Rivest and Stein, Introduction to Algorithms;
Williamson, Shmoys, The Design of Approximation Algorithms;
Motwani and Raghavan, Randomized Algorithms.
Assessment
Exam (65%, duration: 2 hours and 30 minutes) in the summer exam period.
Coursework (35%) 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: 15
Average class size 2019/20: 15
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
