- Industry-relevant curriculum, delivered online or on-site lectures.
- The programme offers exposure to state-of-the-art data analysis/ visualization tools such as R, SAS, Python and Tableau.
- Practitioner-oriented insights from industry experts will help you develop solutions to real-world problems using cutting edge analytical techniques.
- The Dissertation (Project Work) in the final semester enables students to apply concepts and techniques learnt during the programme.
- The programme uses a Continuous Evaluation System that assesses the learners over convenient and regular intervals. Such a system provides timely and frequent feedback and helps busy working professionals stay on course with the programme.
- The education delivery methodology is a blend of classroom and experiential learning. Experiential learning consists of lab exercises, assignments, case studies and work-integrated activities.
- Participants who successfully complete the programme will become members of an elite & global community of BITS Pilani Alumni.
Programme Curriculum Participants need to take at least 12 courses towards coursework, and complete one Project/ Dissertation. The coursework requirement for the programme would consist of a set of core courses and electives. Core courses are compulsory for all participants, while electives can be chosen based on individual learning preferences.
The programme offers a degree of customisation to address the specific L&D needs of your organisations.
- Management Information Systems
- Models and Applications in Operational Research
- Introduction to Statistical Methods
- Financial Management
- Business Data Mining
- Supply Chain Management
- Introduction to Data Science
- Advanced Statistical Methods
- Big Data Analytics
- Predictive Analytics
- Optimization Methods for Analytics
- Analytics for Competitive Advantage
- Elective 1
- Elective 2
- Elective 3
- Project Work
- Elective 4
- Advanced Financial Modeling
- Data Visualization
- Financial Risk Analytics
- HR Analytics
- Investment Banking Analytics
- Marketing Analytics
- Marketing Models
- Retail Analytics
- Supply Chain Analytics
- Real-time Analytics
- Text Analytics
LECTURES DELIVERED ONLINE AND ONSITE
Lectures are delivered by BITS Pilani faculty members through live via online classes, or at the organisation's premises, and are designed to offer similar levels of interactivity as regular classrooms at the BITS Pilani campus.
Learners can access engaging learning material at their own pace which includes recorded lectures from BITS Pilani faculty members, course handouts and recorded lab content where applicable
Continuous Assessment includes graded Assignments/ Quizzes, Mid-semester exam, and Comprehensive Exam.
The programme emphasises on Experiential Learning that allows learners to apply concepts learnt in the classroom in simulated, and real work situations. This is achieved through:
Data analysis/ visualization tools such as Linear Optimization, Descriptive Statistics, Multivariate Analysis & Mining Algorithms using R, Python, Excel and Excel Solver.
CASE STUDIES AND ASSIGNMENTS
Carefully chosen real-world cases & assignments are both discussed and used as problem-solving exercises during the programme.
DISSERTATION/ PROJECT WORK
The fourth semester offers an opportunity for learners to apply their knowledge gained during the programme to a real-world like complex project. The learner is expected to demonstrate understanding of vital principles learnt across semesters and their ability to successfully apply these concepts.
Minimum eligibility to apply: Working professionals holding B.Sc./ M.Sc./ B.E./ MCA/ MBA or equivalent are eligible to apply. Applicants with other qualifications such as B.Com. etc. may apply provided they have done a basic mathematics/ statistics at both 10+2 and Undergraduate level. At least 60% aggregate marks and minimum one year of work experience after the completion of the degree in relevant domains.
The programme is designed for:
- Analysts who wish to hone their technical skills in Statistics and IT
- Statisticians who want to pick up programming skills and domain knowledge
- IT professionals who need to hone their quantitative knowledge and domain understanding