COURSE CURRICULUM

The Master of Science in Data Analytics provides a structured curriculum designed to develop core competencies and advanced skills in the field. In the first semester, students engage with programming for data analysis, where they gain essential coding skills for data manipulation and computational tasks. This is accompanied by statistics for data analytics, covering foundational statistical techniques and methodologies necessary for interpreting and analyzing data accurately. Students also study machine learning and pattern recognition, learning to apply models and algorithms that detect patterns, make predictions, and classify data in real-world contexts.During the second semester, students further their expertise with advanced data and network mining, which focuses on uncovering complex relationships and patterns in large datasets and networked data. The module on data storage solutions for data analytics equips students with the knowledge needed to manage and optimize large-scale data storage systems, enabling efficient data retrieval and analysis. Data visualisation introduces techniques for presenting complex data in a clear and meaningful way, enhancing communication and decision-making. Additionally, applied research methods prepares students to design and carry out research projects using appropriate methodologies, analytical tools, and ethical frameworks.In the third semester, students complete an applied research project that allows them to explore a specific data-driven challenge or area of interest. This capstone project synthesizes learning from previous modules and provides an opportunity to demonstrate their ability to conduct independent research, apply analytical techniques, and deliver actionable insights. The project may be carried out in collaboration with industry partners or based on academic research, offering a practical and impactful conclusion to the program. The course as a whole blends theoretical knowledge with hands-on practice, equipping graduates with the technical and analytical skills necessary for careers in data science, business intelligence, and analytics-driven industries.