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MSc (Data Science)
programme Overview
Mastering the Power of Data
The MSc (Data Science) program is designed to equip students with comprehensive knowledge and hands-on skills in data collection, processing, analysis, and visualization. It combines foundational principles with cutting-edge techniques in statistics, machine learning, big data, and data engineering. This industry-aligned program enables students to make data-driven decisions and build impactful solutions for diverse sectors like healthcare, finance, retail, and government. Through practical labs, live projects, and internships, students evolve into proficient data scientists ready to tackle real-world challenges.2 Years
Duration of program
PG
Level of Study
Faculty Overview
Mastering the Power of Data
The MSc (Data Science) program is designed to equip students with comprehensive knowledge and hands-on skills in data collection, processing, analysis, and visualization. It combines foundational principles with cutting-edge techniques in statistics, machine learning, big data, and data engineering. This industry-aligned program enables students to make data-driven decisions and build impactful solutions for diverse sectors like healthcare, finance, retail, and government. Through practical labs, live projects, and internships, students evolve into proficient data scientists ready to tackle real-world challenges.2 Years
Duration of program
PG
Level of Study
Key Highlights
Advanced Data Analytics Training
Real-Time Projects and Internships
Machine Learning and Big Data Focus
Industry Tools: Python, R, SQL, Tableau
Job-Ready Curriculum with Capstone
HOW WILL YOU BENEFIT
Master data analysis, modeling, and visualization using Python, R, and advanced tools.
Gain experience in handling structured and unstructured data using real-world datasets.
Build machine learning models to solve practical business and societal challenges
Enhance your problem-solving, storytelling, and communication skills for data-driven decision-making.
WHAT WILL YOU STUDY
- Foundations of Data Science: Understand core concepts of data handling, preprocessing, and basic analytics using Python and R.
- Statistical Methods and Probability: Learn probability distributions, hypothesis testing, and inferential statistics essential for data analysis.
- Machine Learning Techniques: Study classification, regression, clustering, and ensemble methods using real datasets.
- Big Data Technologies: Explore tools like Hadoop, Spark, and NoSQL databases for handling large-scale data.
- Apply statistical, analytical, and machine learning techniques to extract insights from complex datasets.
- Build scalable data pipelines and models for business intelligence and automation.
- Communicate insights effectively using visual tools and storytelling techniques.
- Collaborate in interdisciplinary teams to solve data-driven problems.
- Stay updated with emerging trends and technologies in data science.
- Proficiency in Python, R, SQL, and visualization tools.
- Capability to handle structured, semi-structured, and unstructured data.
- Competence in applying data science for predictive modeling and decision-making.
- Strong foundation for research, doctoral studies, or industry certifications.
- Preparedness to work in data science roles across diverse industries.
- Produce globally competitive data science professionals aligned with current and future industry needs.
- Foster a deep understanding of data ethics, privacy, and responsible AI practices.
- Encourage innovation, analytical thinking, and problem-solving through data exploration.
- Prepare graduates for leadership roles in data teams, analytics consulting, and research.
- Promote entrepreneurial thinking to create data-driven solutions and products.
CURRICULUM
CAREERS AND EMPLOYBILITY
Data Scientist / Machine Learning Engineer
Data Analyst / Business Intelligence Expert
Big Data Engineer / Data Engineer
Researcher / Data Science Consultant / Entrepreneur
ELIGIBILITY CRITERIA
Graduates with a Bachelor's degree in Computer Science, Statistics, Mathematics, IT, Engineering.
Commerce or any related field with a minimum of 50% marks are eligible to apply.
