Computer Science

Solving problems in areas such as business, biology, physics, chemistry, engineering, humanities, and social sciences often requires manipulating, analysing, and visualising data through computer programming. This course teaches students with little or no background in computer programming how to design and write small programs using a high-level procedural programming language, and to solve simple problems using these skills. On completion of this subject the student is expected to: 1.Use the fundamental programming constructs (sequence, alternation, selection) 2.Use the fundamental data structures (arrays, records, lists, associative arrays) 3.Use abstraction constructs such as functions 4.Understand and employ some basic program structures 5.Understand and employ some basic algorithmic problem solving techniques 6.Read, write, and debug simple, small programs

This course focuses on the technical solutions needed to improve the fairness, accountability, and transparency of machine learning models. It reflects on the benefits and risks of machine learning models to develop methods to detect and mitigate biases and create solutions to make the inner workings of models more transparent. Topics include statistical notions of fairness and bias; the intended usage of machine learning models; learning fair representations; model interpretability and transparency; generating and evaluating model explanations; and probing representations for bias. Knowledge of machine learning (probability theory, linear algebra, classification) and programming is a prerequisite.

The course provides a theoretical understanding and practical skills related to object-oriented programming. Practical skills will be learnt using the C++ programming language. The course enables students to tackle complex programming problems, making good use of the object-oriented programming paradigm to simplify the design and implementation process.

This course offers the opportunity for students to implement cloud computing related ideas and complete the projects as groups. In this course, students also complete market and feasibility analyses. The goal of this course is to encourage students to create a product that can be successfully marketed.