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5 May 2017: Introduction to Prolog. The structure of a Prolog program and how to use the Prolog interpreter. ... Difference structures. Difference lists: introduction and application to example programs. Building on Prolog.

5 May 2017: They should appreciate the value of other tools and the difference between incidental and intrinsic complexity. ... They should understand the software development life cycle and its basic economics.

20 Jun 2017: A partial function is partial recursive if and only if it is computable. ... understand the notion of coding programs as data, and of a universal machine;.

5 May 2017: Fourier representations. Inner product spaces and orthonormal systems. Periodic functions and Fourier series. ... Wavelets. Introduction to wavelets, with applications in signal processing, coding, communications, and computing.

20 Jun 2017: Concurrent and Distributed Systems (continuing).

31 Oct 2017: Group II. Paper 5. Environmental economics and law. Principles of environmental economics and law, environmental policy and policy analysis, urban and rural environmental management. ... Group III. Paper 12. Law and economics. The relationship between

20 Jun 2017: Taken by:No. of lectures 8. Suggested hours of supervisions: 2. Prerequisite course: Economics and Law. ... Company formation. Brief introduction to business law; duties of directors. Shares, stock options, profit share schemes and the like.

5 May 2017: Prerequisite courses: Security I; Probability; Economics, Law and Ethics; Operating Systems; Computer Networking. ... It also covers the interaction of security with psychology and usability; anonymity; security economics, and aspects of physical security

20 Jun 2017: Simple, uninformed search algorithms. Tree search and graph search. [1 lecture]. Search II. ... 1 lecture]. Neural Networks II. Multilayer perceptrons and the backpropagation algorithm. [1 lecture].

20 Jun 2017: Algorithms and problems. Complexity of algorithms and of problems. Lower and upper bounds. ... Time complexity. Time complexity classes. Polynomial time problems and algorithms. P and NP.