This module provides an in-depth understanding of algorithm analysis, advanced data structures and sophisticated algorithm design techniques. Students will learn to optimize computational tasks through practical applications, project work, and theoretical studies. The course will prepare students to tackle complex problems with efficiency.

This module introduces learners to the concepts, techniques, and applications of data mining. The module will cover the entire data mining process, from data preparation and exploration to model building and evaluation. Learners will explore extracting valuable knowledge and gain insights from large datasets to solve real-world business problems. They will also gain practical experience using data mining tools and software.

This module introduces learners to methods and techniques for analysing problematic organisational situations. They will learn how to analyse business requirements, model systems, and design solutions that meet organizational needs. They will be exposed to both technical and organisational material to provide the knowledge and skills necessary to design and implement an operational system.

This module introduces learners to basic concept and fundamental principles of cloud computing and development platforms. They learn programming skills in cloud, design and develop cloud applications in various platforms. They are exposed to the technologies used in provisioning clouds, the application of cloud computing to solve problems, and the issues that must be considered when deploying cloud technologies in an organisation.

This module equips learners with the skills and knowledge to develop and deploy full-stack web applications.  It covers both front-end and back-end technologies, focusing on building dynamic and secure web applications Learners will gain proficiency in both front-end and back-end development, covering user interface (UI) design, web development frameworks, databases, server-side programming, and application deployment.

This module introduces learners to the fundamental concepts and tools used in data science. They will gain an understanding of the data science workflow, explore data collection, manipulation, analysis, and visualization techniques. Ethical considerations, policies, and legislations for data science will be introduced. The course will also equip learners with essential skills for data science applications.

This module introduces learners to introduce important concepts in machine learning and important algorithms and techniques in this field. They are exposed to data pre-processing, regression, classification, neural networks, tree learning, kernel methods, clustering, dimensionality reduction, ensemble methods, and large-scale ML. They learn how to design and implement machine learning and deep learning models for data analysis using Python.

This module introduces learners to the fundamental concepts and applications of Artificial Neural Networks (ANNs). They will gain theoretical knowledge of neural network architectures, learning algorithms, and optimization techniques. They will also develop practical skills in building and training neural networks for various tasks using popular deep learning libraries.