Learning Outcomes

• Technical Skills

Upon completion of the programme, students will demonstrate proficiency in programming languages commonly used in data science and artificial intelligence, such as Python and be able to apply mathematical and statistical concepts to analyze and interpret data effectively. They will also be able to demonstrate knowledge of machine learning algorithms and techniques to solve data-driven problems.

• Data Analysis and Interpretation

Students will be able to collect, clean, and preprocess data from various sources for analysis, interpret, and communicate insights effectively using data visualization techniques as means of informing decision making processes.

• Machine Learning and AI

Students will demonstrate knowledge in fundamental machine learning concepts, including supervised or unsupervised learning, regression, classification, clustering, and developing machine learning models using appropriate algorithms and techniques. They will also be able to apply artificial intelligence principles to develop intelligent systems capable of learning from data.

• Problem-solving Skills

Students will be able to identify and define data-driven problems in diverse domains, design and implement effective solutions using data science and AI techniques, in addition to evaluating and improving the performance of applied solutions.

• Ethical Awareness and Responsible AI

Upon graduation, students will be able to recognise ethical considerations and biases inherent in data and AI applications. They will be able to apply ethical frameworks to guide decision-making, mitigate potential risks, and design AI systems that prioritize fairness, transparency, and accountability.