Master of Science (M.Sc) in Data Science

After 3 years of successful completion of the programme, 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.

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.

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.