Master of Science in Data Science (M.Sc. DS)

Programme Overview

Kristu Jayanti (Deemed to be University), Bengaluru, offers a two-year, full-time Master of Science in Data Science (M.Sc. DS) programme. Established in 2023, the programme is designed to develop skilled Data Science professionals through an integrated curriculum that combines Machine Learning, Big Data Analytics, and Statistics. This foundation in decision sciences, research, and globally relevant industry applications equips students to excel in data-driven roles across diverse sectors.

Eligibility

  • Candidates with B.Sc. Data Science / B.Sc. Data Analytics / B.Sc. Computer Science / BCA / BE / B.Tech. or B.Sc. Mathematics / Statistics / Physics / Electronics with not less than 50% (45% for SC/ ST candidates) marks as aggregate are eligible to apply. Candidates who do not have a background in Computer Science will be required to undergo a mandatory Bridge Course in Computer Science conducted by the Institute.

Why choose this programme?

  • Industry-relevant curriculum
  • Hands-on learning
  • Strong foundations
  • Experienced faculty
  • Placement & industry links
  • Interdisciplinary exposure
  • Research & innovation focus

What you will learn

By the end of the programme, you will be able to:

Core technical skills

  • Pre-process, clean and visualise large, messy datasets.
  • Implement statistical models and modern machine learning algorithms.
  • Build and evaluate predictive and prescriptive models.
  • Work with relational and non-relational databases; design data pipelines.
  • Use cloud platforms and container technologies for model deployment.
  • Program in Python/R and use libraries such as Pandas, scikit-learn, TensorFlow/PyTorch (or equivalents).

Analytical & professional skills

  • Translate business problems into data questions and measurable KPIs.
  • Interpret model results and communicate findings clearly to non-technical stakeholders.
  • Apply ethics and responsible AI principles to data projects.
  • Manage projects using reproducible workflows, version control and unit testing.

Domain & research skills

  • Apply data-driven methods to domain problems (finance, healthcare, marketing, etc.).
  • Design and execute an end-to-end capstone project that includes a literature review, methodology, experimentation and reporting.

Student Enrichment Activities

  • National-level Data Science Hackathons
  • Kaggle & Datathon participation
  • Workshops on Python, R, TensorFlow, PyTorch & SQL mastery
  • Cloud certification bootcamps
  • Guest lectures by industry experts from MNCs
  • Peer mentoring by senior students
  • Interdisciplinary analytics projects

Placement & Career Support

  • Technical training for Python, SQL, Statistics, ML, AI
  • Soft skills, interview etiquette, GD & mock tests
  • Analytics interview prep (case studies, business problems)
  • Domain-based interview practice (FinTech, Retail, Healthcare)
  • Project-based portfolio development
  • Opportunities for internships at analytics firms

Career Prospects

M.Sc. Data Science graduates are in demand across industries that rely on data-driven decision-making.

Typical Job Roles

  • Data Scientist
  • Data Analyst / Business Analyst
  • Machine Learning Engineer
  • Data Engineer / Big Data Engineer
  • Research Analyst / Quantitative Analyst
  • AI Engineer / Deep Learning Engineer
  • Analytics Consultant
  • BI Developer / Visualization Specialist
  • MLOps Engineer
  • Product Analyst

Industry Sectors

  • Information Technology & Product Companies
  • Finance, Banking & FinTech
  • Healthcare & Life Sciences
  • Retail, E-commerce & Supply Chain
  • Telecommunications & Media
  • Government & Public Sector Analytics
  • Start-ups & Research Labs
  • Consulting & Professional Services

Programme Matrix

Sem. Course Type Course Title Credits
I DSC Statistical Data Analysis using R 4
I DSC Mathematics for Data Science I 4
I DSC Advanced Database Management System 4
I DSC Data Structures and Algorithms using Python 4
I DSC Web Technologies Practical 2
I DSC Advanced Database Management System Practical 2
I DSC Data Structures and Algorithms using Python Practical 2
I SEC Python for Data Science 4
II DSC NoSQL Databases 4
II DSC Mathematics for Data Science II 4
II DSC Statistical Inference 4
II DSC NoSQL Databases Practical 2
II DSC Data Manipulation and Statistical Analysis Practical 2
II DSE Cloud Computing 4
II DSE Soft Computing 4
II DSE Natural Language Processing 4
II DSE Information Security 4
II DSP Capstone Project 2
II SEC Soft Skills 4
III DSC Big Data Analytics 4
III DSC Machine Learning 4
III DSC Data Visualization 4
III DSC Machine Learning Practical 2
III DSC Data Visualization Practical 2
III DSP Big Data Analytics Project 2
III DSE AI driven Cloud and Edge Computing 4
III DSE Deep Learning Techniques 4
III DSE Generative AI and LLM 4
III DSE Cyber Security 4
III MDC Generic Elective 3
III SEC Research Methodology 2
IV DSC Computer Vision and NLP 4
IV DSP Major Project 8
IV DSE Quantum Computing 4
IV DSE Blockchain Technologies 4
IV DSE Drone Programming 4
IV DSE Internet of Things 4
IV SEC Research Proposal Writing and Literature Review 2