B.Sc. Data Analytics

In the second semester, students advance to specialised topics. The curriculum includes data collection, management techniques, and advanced statistical methods. Students explore machine learning fundamentals, data mining, and storage solutions. Business intelligence is also introduced to students, providing insights into data-driven decision-making. An elective allows students to tailor their studies to specific interests, enhancing their learning experience and preparing them for more focused study in future semesters.

The third semester builds on prior knowledge with predictive analytics and database management courses. Students develop practical skills using data analytics tools and technologies and gain hands-on experience with programming for data analysis. The curriculum includes research methodology and a second elective, providing students with in-depth exploration and specialisation opportunities. This semester emphasises applying theoretical knowledge to practical scenarios and refining analytical skills.

During the fourth semester, students delve into advanced topics such as big data analytics and statistical modelling. Courses cover data cleaning, preparation, and critical data ethics and privacy issues. Students also have the chance to select an open elective and an additional elective, allowing for further customisation of their studies and exploration of specific areas of interest, building on their foundational knowledge and skills.

In the fifth semester, students analyse data trends through time series analysis and advanced visualisation techniques. The curriculum includes courses on text analytics, natural language processing, and cloud computing for data management. Open and additional electives offer further specialization opportunities, enabling students to explore areas of interest in depth. This semester emphasises advanced analytical techniques and practical data management skills.

The sixth semester features a capstone project integrating the knowledge acquired throughout the programme. Students study advanced machine learning algorithms, business analytics, and optimisation techniques. Additional and open electives provide opportunities for further study and exploration of specialised topics. This semester is designed to apply theoretical knowledge in practical settings, preparing students for professional roles and advanced data analytics tasks.

In the seventh semester, students gain practical experience through an industry internship. The focus is on applying data analytics skills in real-world settings, including decision-making and marketing. Students can choose an open elective to explore their interests further. This semester emphasises hands-on learning and professional development, preparing students for careers in data analytics and providing valuable industry experience.

The final semester includes advanced courses on data analytics strategies and predictive modelling. Students explore applications in health and medicine and engage in professional development and career planning. The last elective provides the final opportunity for specialised learning. This semester is designed to consolidate knowledge, refine skills, and prepare students to transition to professional roles or further academic pursuits.