Foundational Mathematics equips students with the essential mathematical skills required for success in the Applied Data Science and Artificial Intelligence curriculum. The course identifies individual learning needs through a series of diagnostic quizzes and supports personalised development through targeted self-study. Students are required to take a formal mathematics exam at the end of the first block, which contributes to the overall assessment of that block.

The course begins with ungraded quizzes that assess key mathematical domains. Based on their performance, students receive tailored recommendations for review materials to help them strengthen specific concepts before the final exam. Although the quizzes do not count toward the final grade, they play a critical role in guiding students toward the required level of proficiency. Successful completion of the course ensures students are mathematically prepared for more advanced modules in the programme.

The course begins with formulating a research question and problem statement, emphasizing how to define the scope of inquiry—narrowing overly broad topics or expanding overly narrow ones. Students will then learn how to identify credible data sources, collect relevant data, and recognize various data formats. Key data preparation skills will be developed, including cleaning techniques and introductory data analysis. Students will use tools like Excel to perform descriptive statistics and explore patterns in the data. Next, students will learn how to create effective visualizations using Power BI, gaining insight into the appropriate use of different chart types based on data and context. They will interpret their visualizations to draw meaningful conclusions, identify limitations, and propose future directions for their research. The course concludes with a focus on communication and presentation skills, culminating in a final demonstration where students present their dashboards and insights to their peers.