M.Sc. Data Science

• Strong academic reputation of SBU and domain expert faculty.
• Industry linked curriculum and specializations.
• Blended learning environment with modern lab facilities.
• Opportunity for student exchange programme with International / National partner universities / institutes.
• Opportunity for on-the-job training through industry internship programmes.
• Limitless research opportunities and innovations.

Objectives

• To provide a strong foundation for core data science principles.
• To develop advanced analytical and computational skills.
• To foster problem-solving and critical thinking skills.
• To encourage practical and hands-on experience in data science.
• To prepare students for a variety of career opportunities in data science.
• To encourage research and innovation in data science and applications.

Program Outcomes

The program outcomes of an M.Sc. in Data Science are the knowledge, skills, and abilities that students are expected to have after completing the course. These outcomes are broadly equivalent with the essential competences required for a successful career in data science, and they paint a clear picture of the skills that students will acquire. The following are typical program outcomes for an MSc in Data Science.

• Advanced Data Analysis and Interpretation
• Machine Learning and AI Techniques
• Data Engineering and Management
• Programming and Computational Skills
• Statistical and Mathematical Foundations
• Data Visualization
• Critical Thinking and Problem-Solving
• Research and Innovation

1. Programme Educational Objectives (PEOs)

• PEO 1: Equip graduates with a strong foundation in mathematics, statistics, and computer science essential for data analysis.
• PEO 2: Prepare graduates to proficiently use programming languages and tools for data manipulation, analysis, and visualization.
• PEO 3: Develop graduates' ability to apply analytical and critical thinking skills to solve complex data-driven problems in various domains.
• PEO 4: Foster practical experience through projects and internships, ensuring graduates are prepared for careers in data science and analytics.

2. Program Outcomes (POs)

After completing the course, the students will be able to:

• PO 1: Graduates will demonstrate a solid understanding of fundamental mathematical, statistical, and computer science concepts essential for effective data analysis and interpretation.
• PO 2: Graduates will possess the analytical skills required to solve complex problems using statistical methods, linear algebra, and calculus, supporting data-driven decision-making.
• PO 3: Graduates will be proficient in programming languages such as Python and R, using them effectively for data manipulation, analysis, modelling, and visualization.
• PO 4: Graduates will be able to design, implement, and query both SQL and NoSQL databases, ensuring efficient data storage, retrieval, and management.
• PO 5: Graduates will apply machine learning algorithms including supervised and unsupervised techniques—to real-world datasets for predictive modeling and pattern recognition.
• PO 6: Graduates will utilize data mining techniques to uncover meaningful patterns and insights from large and complex datasets.
• PO 7: Graduates will perform hypothesis testing, regression analysis, and related statistical methods to inform and support sound decision-making.
• PO 8: Graduates will understand and implement deep learning models such as neural networks, convolutional neural networks (CNNs), and recurrent neural networks (RNNs) for advanced analytics tasks.
• PO 9: Graduates will demonstrate knowledge and practical skills in big data technologies and frameworks (e.g., Hadoop, Spark) for efficient processing and analysis of massive datasets.
• PO 10: Graduates will effectively visualize data and communicate insights clearly to stakeholders using appropriate tools and storytelling techniques.
• PO 11: Graduates will recognize and uphold ethical standards related to data privacy, security, and fairness, ensuring responsible data science practices.
• PO 12: Graduates will engage in continuous learning to stay updated with evolving data science technologies and methodologies, supporting long-term professional development.

3. Programme Specific Outcomes (PSOs)

• PSO 1: Graduates will apply statistical techniques and data mining methods to analyze complex datasets, extract meaningful insights, and support informed decision-making.
• PSO 2: Graduates will demonstrate expertise in programming languages such as Python and R, and effectively design, implement, and manage SQL and NoSQL databases for data manipulation, analysis, and storage.
• PSO 3: Graduates will implement supervised and unsupervised machine learning algorithms to solve real-world problems and enhance data-driven analytical capabilities.

The two-year full time M.Sc. Data Science programme is structured very carefully in order to create an academic, experiential and transformational learning environment. The detailed course structure of the course can be downloaded from the following link:

Eligibility

Candidate must have completed bachelor’s degree B.Sc./ BCA / B.Tech / B.E/ B.Com / BA with atleast 55% marks in aggregate including 10+2 Mathematics as compulsory subject. (5% relaxation marks in case of candidates belonging to SC/ST category).

At Sarala Birla University, believe that hands-on experience is the key to succeed in the fast growing field of data science. Our M.Sc. Data Science Internship Program with International / National partner universities / institutes is intended to give students significant opportunity to use their academic knowledge in real-world situations, engage with industry leaders, and further progression of careers.

Key Features of the Internship Program:

• Industry Collaborations
• Real-World Experience & Personalized Internship Placement
• Strong Support and Mentorship
• Global Internship Opportunities

Career Opportunities

Sarala Birla University is having an active placement cell working through out for maintaining good placement record. The placement cell is credited for taking active participation in selection of companies visiting the University for Campus recruitment. It is supported by active placement committee members who have rich industry experience and valuable linkages in the corporate world. Mandatory personality development classes have been introduced, in which students are trained for public speaking, presentations, self- assessment exercises etc.

Students are also able to opt internship program in their respective fields. Few career opportunities are as follows:

• Data Research Scientist
• Data Scientist (Digital Marketing, Healthcare etc.)
• Data Science Consultant
• Data Privacy Officer
• Quantitative Analyst (Quant)
• Jobs in PSU
• UPSC (IAS, IPS, IFS, IRS)
• State govt. Jobs
• Defence Sector
• Social Sector
• Entrepreneurship