Master of Data Analytics in Data Analytics

COURSE CURRICULUM

The data science program is structured over four semesters, each designed to progressively build students’ skills in programming, data analysis, and advanced analytics techniques. In the first semester, students are introduced to the fundamentals of programming and data science. Alongside this, they study quantitative methods to develop a solid foundation in mathematical and statistical concepts. They also select an additional subject from the analytics stream, minor, or elective options, allowing them to tailor their studies based on interest.In the second semester, students focus on developing their ability to analyze complex data sets. Core subjects such as Linear Models and Applied Econometrics equip them with essential tools for understanding and modeling data relationships. Students also choose two more subjects from the analytics, minor, or elective options, further broadening their knowledge and allowing for specialization.By the third semester, students deepen their expertise in data science techniques. They study advanced subjects including Statistical Learning and Regression Models, Infrastructure for Data Analytics, and Advanced Machine Learning. These courses provide both theoretical knowledge and practical skills needed to handle large-scale data and develop predictive models.In the final semester, students consolidate their learning through an Applied Data Analytics Project, which offers hands-on experience working on real-world data challenges. They also study Deep Learning Through Neural Networks, exploring cutting-edge methods in artificial intelligence. To complete their program, students select one final subject from the analytics, minor, or elective options, allowing them to tailor their studies to their career goals. Overall, the program offers a balanced combination of foundational knowledge, practical skills, and advanced techniques to prepare students for careers in data science and analytics.