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M.Sc. Programmes

DEGREE PROGRAMMES M.Sc. BUSINESS ANALYTICS

M.Sc. Business Analytics

M.Sc. Business Analytics is a five-semester Work Integrated Learning Programme designed for working professionals, who are aspiring for rapid career progression in the high-growth areas of Business Analytics and Big Data, and wish to stand out in highly competitive workplaces by acquiring prestigious Master’s-level qualification from a premier institution.

 

 

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  • Programme Highlights
  • UGC Approval
  • Programme Curriculum
  • Learning Methodology
  • Eligibility Criteria
  • Fee Structure
  • How to Apply
Programme Highlights
  1. The programme is offered by BITS Pilani, a top-ranked institution, recently announced as an Institution of Eminence by MHRD, Govt. of India

  2. The programme is of five semesters, and can be pursued without a career break

  3. Classes will be conducted by BITS Pilani faculty over weekends through live online sessions

  4. The programme offers exposure to state-of-the-art data analysis/ visualization tools such as R, SAS, Python and Tableau

  5. Practitioner-oriented insights from industry experts will help you develop solutions to real world problems using cutting edge analytical techniques

  6. The programme emphasizes on experiential learning through Simulations, Online Labs, Case Studies, Group Discussions, Assignments and Project work

  7. Dissertation/ Project Work in the final semester enables learners to apply concepts and techniques learnt during the programme









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UGC Approval

BITS Pilani is an Institution of Eminence under UGC (Institution of Eminence Deemed to be Universities) Regulations, 2017. The Work Integrated Learning Programmes (WILP) of BITS Pilani constitutes a unique set of educational offerings for working professionals. WILP are an extension of programmes offered at the BITS Pilani Campuses and are comparable to our regular programmes both in terms of unit/credit requirements as well as academic rigour. In addition, it capitalises and further builds on practical experience of students through high degree of integration, which results not only in upgradation of knowledge, but also in up skilling, and productivity increase. The programme may lead to award of degree, diploma, and certificate in science, technology/engineering, management, and humanities and social sciences. On the recommendation of the Empowered Expert Committee, UGC in its 548th Meeting held on 09.09.20 has approved the continued offering of BITS Pilani’s Work Integrated Learning programmes.

Programme Curriculum

First semester

  • Marketing

  • Management Information Systems

  • Models and Applications in Operational Research

  • Introduction to Statistical Methods

Second Semester

  • Financial Management

  • Business Data Mining

  • Supply Chain Management

  • Introduction to Data Science

Third Semester

  • Advanced Statistical Methods

  • Big Data Analytics

  • Predictive Analytics

  • Optimization Methods for Analytics

Fourth Semester

  • Analytics for Competitive Advantage

  • Elective 1

  • Elective 2

  • Elective 3

Fifth Semester

  • Elective 4

  • Project

Electives

  • 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

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For more information on programme curriculum download the programme brochure

Electives finally offered will be at the discretion of the BITS Pilani, and will be decided in consultation with HCL. Offered electives will be made available to enrolled students at the beginning of each semester.

Learning Methodology
Online lectures

CLASSROOM SESSIONS

  • Classroom sessions in this programme will be conducted through live online sessions which can be accessed by the learners from any location using a computer and a high-speed internet connection.

  • Classes will be conducted by BITS Pilani faculty over weekends. A typical weekend classroom session per subject is of 1.5-2 hours duration. Since students typically pursue 4 courses in a semester, they will be expected to attend approximately 4 classroom sessions over a weekend.

  • These classroom sessions will be typically scheduled over 16 weekends per semester.

  • The schedule of the classroom sessions, will be announced at the beginning of each semester.

Digital Learning

DIGITAL LEARNING

Learners can access engaging learning material at their own pace which lecture videos, student notes, curated content etc. for select courses, through a learning management platform that is engaging and mobile-friendly.

Project work

PROJECT WORK

During the final semester participants carryout a semester-long intensive project work applying the various concepts learnt throughout the program guided by the organisation mentor and supervisor. Participants are provided access to virtual labs where applicable, and faculty expertise to support the project work.

experimental Learning

EXPERIENTIAL LEARNING

The programme emphasises on Experiential Learning that allows learners to apply concepts learnt in classroom in simulated and real work situations. This is achieved through Simulations, Online Labs, Case Studies, Group Discussions, and Assignments, etc.

The programme covers Data analysis/ visualization tools such as Linear Optimization, Descriptive Statistics, Multivariate Analysis & Mining Algorithms using R, Python, Excel and Excel Solver

Continour Assessment

EXAMINATIONS & CONTINUOUS ASSESSMENT

The learners’ performance is assessed continuously throughout the semester using various tools such as quiz, assignments, mid-semester and comprehensive exams. The assessment results are shared with the learners to improve their performance.

Each course will entail a minimum of 1 Assignment/ Quiz, a Mid-semester exam and a final Comprehensive exam. Your semester calendar will clearly indicate the dates of the Mid-semester and Comprehensive exam. Typically, a Mid-semester or Comprehensive examination for a course is for 2-3 hours duration. The examinations are typically conducted over a weekend, i.e. Saturday and Sunday.

Eligibility Criteria

Minimum eligibility to apply: Working professionals holding B.E./ B.Tech./ M.Sc./ MCA with atleast 60% aggregate marks or more in their qualifying exam and minimum two years of work experience within HCL in relevant domains are eligible to apply.

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

The above are only the minimum criteria to apply. Your profile will also need to be shortlisted and approved by HCL Technologies after checking all of the Eligibility Criteria as per HCL's Higher Education policy. The final decision to offer admission to an applicant rests with BITS Pilani which will be made based on an overall review of your application information.

Fee Structure

  • The following fees schedule is applicable for candidates seeking new admission during the academic year 2023-24

    Application Fees (one time) : INR 1,500

    Admission Fees (one time) : INR 16,500

    Semester Fees (per semester) : INR 63,500

  • The one-time Application Fee is to be paid at the time of submitting the Application Form through the Online Application Centre.

  • Admission Fee (one-time) and Semester Fee (for the First Semester) are to be paid together once admission is offered to the candidate. Thus, a candidate who has been offered admission will have to pay Rs. 80,000/-. You may choose to make the payment using Netbanking/ Debit Card/ Credit Card through the Online Application Centre.

  • Semester Fee for subsequent semesters will only be payable later, i.e. at the beginning of those respective semesters.

  • Any candidate who desires to discontinue from the programme after confirmation of admission & registration for the courses specified in the admit offer letter will forfeit the total amount of fees paid.

  • All the above fees are non-refundable.

How to Apply

  • Click here to visit the Online Application Center. Create your login at the Online Application Center by entering your official HCL Email ID only and create a password of your choice. Once your login has been created, you can anytime access the Online Application Center using your official email ID and password.

  • Begin by clicking on Step 1 - ‘Fill/ Edit and Submit Application Form’. This will enable you to select the programme of your choice. After you have chosen your programme, you will be asked to fill your details in an online form. You must fill all details and press ‘Submit’ button given at the bottom of the form.

  • Now, click on 'Pay Application Fee’ to pay INR 1,500/- using Netbanking/ Debit Card/ Credit Card

  • Finally, click on 'Upload & Submit All Required Documents’. This will allow you to upload one-by-one all the mandatory supporting documents such academic certificates and transcripts, photograph, etc. and complete the application process. Acceptable file formats for uploading these documents are .DOC, .DOCX, .PDF, .ZIP and .JPEG

  • Upon receipt of your Application Form and all other enclosures, the Admissions Cell will scrutinise them for completeness, accuracy and eligibility.

  • Admission Cell will intimate selected candidates by email within two weeks of submission of application with all supporting documents. The selection status can also be checked by logging in to the Online Application Centre.