Master of Science (M.Sc) in Data Science

After 3 years of successful completion of the program, the graduates will:

PEO 01:  Establish themselves as competent Data Science professionals by applying advanced statistical, analytical, and computational techniques to solve complex real-world problems in industry, research, and societal domains.

PEO 02:  Engage in research, innovation, interdisciplinary learning, and continuous professional development through higher studies, certifications, or entrepreneurial initiatives to adapt to emerging technologies and evolving practices in Data Science.

PEO 03:  Demonstrate professional integrity, ethical responsibility, and sensitivity to societal, ecological, economic, and data-governance considerations while designing, developing, and deploying data-driven solutions.

On successful completion of the Program, the students shall be able to:

PO1: Domain Knowledge and Fundamentals: Apply advanced knowledge of mathematics, statistics, computer science, and Data Science principles to analyse, model, and interpret complex datasets.

PO2: Data Analysis and Modelling Skills: Design, develop, and evaluate data-driven models using appropriate statistical methods, machine learning, deep learning, and big data analytics techniques to derive actionable insights.

PO3: Problem Solving and Critical Thinking: Identify, formulate, and solve complex Data Science problems using analytical reasoning, algorithmic thinking, and interdisciplinary approaches.

PO4: Research and Innovation: Conduct independent and collaborative research involving data acquisition, experimentation, evaluation, and scholarly reporting, contributing to innovation and knowledge creation in Data Science.

PO5: Modern Tools and Technologies: Select and effectively use modern Data Science tools, programming frameworks, databases, cloud platforms, and data pipelines for scalable and efficient data-driven solutions.

PO6: Ethics, Professional Responsibility and Sustainability: Apply ethical principles, data privacy regulations, security practices, explainable AI concepts, and sustainability considerations in the development and deployment of data-driven systems.

PO7: Communication and Teamwork: Communicate analytical findings effectively through technical documentation, data visualisations, and presentations, and function efficiently as an individual or as a member of multidisciplinary teams.

PO8: Lifelong Learning and Professional Development: Recognise the need for and engage in continuous learning, professional development, and skill enhancement to adapt to emerging technologies and evolving industry and research requirements.

On successful completion of the Program, the students shall be able to:

PSO 01: Apply advanced statistical, machine learning, and computational techniques to analyse complex datasets and generate validated insights for industry and research applications.

PSO 02: Design, implement, and deploy scalable and secure data-driven solutions using modern programming frameworks, cloud platforms, and data engineering tools.

PSO 03: Demonstrate ethical, professional, and responsible practices by adhering to data governance, privacy, security, and sustainability standards in data-driven systems.