B.Sc. Applied Statistics and Data Analytics
The B.Sc. in Applied Statistics and Data Analytics (ASDA) is a dynamic and interdisciplinary field that combines Computer Science, Data Analytics, Machine Learning, and Statistics. It empowers professionals to collect, analyse, and harness Data and Statistics to derive valuable insights and make informed decisions. This course opens the door to a wide range of opportunities in various sectors that rely on data-driven expertise. Nowadays industries are experiencing unprecedented growth, driven by the development of technology. With this growth comes an increased need for professionals who can navigate and leverage the wealth of data and statistics. As long as data remains the lifeblood of the industry, this course will remain in high demand, poised to shape the future of industries.
It combines coursework in statistics and data analytics with hands-on experience analysing real datasets. Students learn about statistical concepts such as Deep Learning, Real Analysis, Demography, Data Analytics for HRM , Integral Transform , Statistical Computing Using R, Business Analytics, Functions of Complex Variables, Survey Sampling Techniques, Structural Query Language (SQL), Lattice Theory, Bioinformatics, Power BI, Tableau Probability, Statistical Inference, and Regression Analysis, as well as methods for data visualization, Machine Learning, Data Mining, Statistical software and programming languages such as R, Python and gain experience using these tools to analyse data.
Graduates of this programme are well-prepared for careers in fields such as market research, data science, business analytics, or public policy analysis, where they apply their skills to solve real-world problems and make data-driven decisions. They are also well-prepared for post graduate study in statistics, data science, or related fields.
Applications Open for 2025
B.Sc. Applied Statistics and Data Analytics
Information on Scholarship 2025 will be updated shortly. Please check back soon.
Minimum 50% aggregate score in 10+2/Class 12th or in equivalent examination with Mathematics as a subject (at least 45% marks, in case of Reserved Class category candidate belonging to Maharashtra State only)
or
Minimum 55% aggregate score in any Engineering Diploma from any UGC-recognised university
The selection process is based on MIT-WPU CET 2024 Personal Interaction score.
- Highly qualified faculty, with a strong track record of research and publication
- Workshops for hands-on experience in software such as R, SAS, Python, HADOOP, SQL, and SPSS
- Guest lectures, seminars, and workshops by eminent corporate leaders
- MOOCs, skill enhancement and interdisciplinary courses for holistic development
- Industry and teaching internship
- Dedicated Centre for Industry-Academia Partnerships to support students for internships and job placements
- MIT-WPU Technology Business Incubator (TBI) to support early-stage entrepreneurs, and students through funding, mentoring, and network connection.
- Rural, national, and international immersion programmes
- Disciplinary knowledge: Capable of demonstrating comprehensive knowledge of statistics.
- Communication Skills: Ability to express thoughts and ideas effectively in writing and orally.
- Critical thinking: Capability to apply analytic thought to a body of knowledge.
- Problem solving: Capacity to extrapolate from what one has learned and apply their competencies to solve different kinds of non-familiar problems of statistics and data analytics.
- Analytical reasoning: Ability to evaluate the reliability and relevance of evidence.
- Research-related skills: A sense of inquiry and capability for asking relevant/ appropriate questions, problematizing, synthesising and articulating.
- Cooperation/Team work: Ability to work effectively and respectfully with diverse teams.
- Scientific reasoning: Ability to analyse, interpret and draw conclusions from quantitative/qualitative data.
- Reflective thinking: Critical sensibility to lived experiences, with self-awareness and reflexivity of both self and society.
- Information/digital literacy: Capability to use ICT in a variety of learning situations,
- Self-directed learning: Ability to work independently.
- Multicultural competence: Possess knowledge of the values and beliefs of multiple cultures.
- Moral and ethical awareness/reasoning: Ability to use ethical practices in all work.
- Leadership readiness/qualities: Capability for mapping out the tasks of a team.
- Lifelong learning: Ability to acquire knowledge of statistics and data analytics skills.
admissions@mitwpu.edu.in 
