Bachelor of Science (Hons./Hons. with Research) Statistics & Data Science

BSc Statistics and Data Science Course

B.Sc. (Hons./Hons. with Research) Statistics and Data Science is a undergraduate course in the School of Basic and Applied Sciences of SGT University. The program is created according to the NEP 2020 framework with the focus on high levels of theoretical background, practical, data-driven skills, and research orientation.
B.Sc. (Hons./Hons. with Research) Statistics & Data Science is a four-year (eight semesters) course with multiple entry/exist as per the NEP 2020 that combines the traditional statistical knowledge and skills with contemporary data science, analytics and computational methodologies. The curriculum is directed towards students who are interested in the acquisition, analysis, and interpretation of data to facilitate decision making in science, industry, business, technology and public policy.
The multidisciplinary curriculum provides the students with the knowledge of statistical reasoning, models of probability, the analysis of data, the fundamentals of machine learning, and methods of research to prepare them to work in the industry and to continue their education in the higher academic institutions. The program promotes critical thinking, problem solving, ethical data practices and learning based research.

B.Sc. (Hons./Hons. with Research) Statistics & Data Science Modules

The B.Sc. (Hons./Hons. with Research) Statistics & Data Science program includes a wide range of subjects that comprehensively cover statistics, mathematics, computing, and data analytics. Key areas of course modules include:

• Probability Theory and Statistical Inference
• Statistical Modeling and Regression Analysis
• Data Science Foundations and Programming
• Exploratory Data Analysis and Visualization
• Machine Learning and Predictive Analytics
• Big Data Analytics
• Statistical Computing and Software Tools
• Research Methodology and Scientific Writing
• Applied Statistics for Industry and Social Sciences
• Generative AI, Large Language Models, and Prompt Engineering

The program is structured over eight semesters, with progressive learning from fundamental concepts to advanced applications and a mandatory research project in the final year, enabling students to develop independent research competence.

B.Sc. (Hons./Hons. with Research) Statistics & Data Science Subjects

The program combines theoretical rigor with hands-on practical exposure through laboratories, projects, internships, and research work. Some of the core subjects include:

Key Areas of Study:

• Sampling Technique
• Linear Models and Multivariate Analysis
• Statistical Quality Control and Optimization Technique
• Programming with R / Python for Data Analysis
• Database Management and Data Handling
• Machine Learning Techniques
• Time Series Analysis and Forecasting
• SQL with RDBMS
• Research Project / Dissertation

Students are encouraged to undertake industry internships, data-driven projects, and research-based assignments to gain real-world exposure and analytical proficiency.

B.Sc. (Hons./Hons. with Research) Statistics & Data Science Admission 2026

SGT University, a leading institution for science education in India, invites applications for admission to the B.Sc. (Hons./Hons. with Research) Statistics & Data Science program.

Eligibility Criteria:

• 10+2 with Mathematics as a compulsory subject
• Minimum 60% aggregate marks

Top B.Sc. (Hons./Hons. with Research) Statistics & Data Science College in India

SGT University is recognized as one of the emerging institution of excellence in higher education in India, particularly in the Delhi NCR and Haryana region. The university offers: Experienced faculty with strong academic and research backgrounds

• Modern computing laboratories and statistical software facilities
• Industry-aligned curriculum with research orientation
• Strong academic mentoring and career guidance

Students benefit from career-focused training, internships, and research exposure, preparing them for roles in analytics, data science, research, and higher education.