BSc (Hons) Computer Science (Top-up)

This module surveys essential principles, methods, and techniques in AI and machine learning. It covers a broad range of AI topics such as problem solving, knowledge representation, logical and probabilistic inference, and machine learning using methods of automata theory, logics, probability theory and statistics.

It discusses examples of intelligent systems and studies how to develop applications that can learn from experience such as expert systems, automatic classifiers and autonomous systems planning their actions and communicating in natural language. Students will be offered lectures, which introduce key concepts, explain main principles and techniques in AI, and demonstrate how to apply them in areas such as image recognition and price forecasting.

The module enables students to undertake an appropriate, short professional activity related to their course at level 6 with a business or community organisation and to gain credit for their achievements.

The activity can be professional training or certification, a volunteering activity, employment through internal or external work-based placements, research-related activities, business start-up projects, entrepreneurship programs and more. Please see the complete list of accepted activities on WebLearn.

“Finite automata or finite state machines (and their languages) are structures that can be used as abstract models for computational devices, capturing many of their essential features without the complications of hardware considerations.

This module will enable students from the mathematics and computing areas to appreciate the powers and limitations of computers and will introduce them to some of the factors in complier design through development of some of the standard mathematical models of computational devices. The aims of this module are:

• To introduce a range of models of computational devices.
• To investigate the expressive power of different models.
• To introduce the idea of decision problems in mathematics.
• To demonstrate that interesting decision problems in computer science will often be unsolvable

This module introduces a range of specialist programming techniques as applied to mobile platforms. Specific areas of study will include: programming strategies for resource-limited portable devices – including reviewing key components through the development of exemplar applications using an appropriate mobile-based programming platform such as Java ME and Google Android.

The key skills and knowledge to be gained are:

• Understanding theoretical concepts related to the work of software in wireless networks and the use of different protocols, frameworks and tools for building mobile applications
• Learning techniques for programming mobile applications using standard technological frameworks, development tools, mobile device emulators and handsets
• Acquiring practical skills in developing mobile applications which utilize wireless services and mobile Internet
• Applying analytical knowledge and practical skills for building typical mobile applications
• Developing ability to compare protocols, models and paradigms for mobile applications and estimate trade-offs during design using different design patterns, development frameworks and programming techniques
• Building professional competence and increasing the employability through the use of industrial standard technologies and tools for software development

This module equips the students with professional knowledge and skills for developing contemporary data processing systems on the desktop, on the move, on the net, in the cloud and at the edge of the computational infrastructure.

It systematically introduces the principles and models of functioning of modern data processing systems – distributed, parallel, embedded, portable and wearable.

For this purpose, it utilizes the recent advances in infrastructural, technological and methodological support of software development – structured, semi-structured and connected data, wired and wireless communications, containerized and remote tools, cloud and edge platforms, DevOps movements, etc.

The module enables students to demonstrate their acquired knowledge and skills through a systematic and creative investigation of a project work in accordance with their course requirements. The topic of investigation will cover a broad spectrum of various analysis and techniques and will lead to a comprehensive and concise academic/industry-related report.

Students will be assisted in exploring areas that may be unfamiliar to them and encouraged to develop innovative ideas and techniques. Students will be able to choose a project that may require the solution to a specific problem, creation of an artefact in a real-world environment or an investigation of innovative ideas and techniques related to an area within their field of study.

Collaboration with outside agencies and projects with industrial, business or research partners/ sponsors will be encouraged.