Master of Technology (M.Tech.) Machine Learning and Data Science Syllabus 2025: Subjects, Specializations, and Semester-wise Syllabus

The M.Tech. in Machine Learning and Data Science syllabus is a comprehensive program designed to equip students with the essential knowledge and skills required to excel in the rapidly evolving fields of machine learning and data science. The curriculum typically encompasses a wide range of subjects, including but not limited to, statistics, linear algebra, data preprocessing, machine learning algorithms, deep learning, natural language processing, computer vision, big data analytics, and ethical considerations in data science. Students can expect to engage in hands-on projects, collaborate on real-world data problems, and gain proficiency in programming languages such as Python and R. Additionally, coursework often delves into advanced topics such as reinforcement learning, generative adversarial networks, and distributed computing. By the end of the program, graduates are not only well-versed in the latest technological advancements but also possess a deep understanding of the ethical and societal implications of data-driven decision-making, positioning them for successful careers in academia, industry, or research.