Vellore Institute of Technology Online MSc Data Science
- AICTE & UGC-recognized
- Strong placement support
- Industry-focused courses
- Global learning exposure
- Research-driven curriculum
About
It is said that organising data is the first step towards gathering knowledge hence data is not just a by-product it drives decisions, innovation, business strategy, and competitive advantage.
From analysing customer behaviour and optimising supply chains to building predictive models and deploying artificial intelligence, careers in data science are at the intersection of technology and business.
If you are someone who enjoys extracting insights from numbers, building models, programming and influencing how organisations use data, the VIT Online M.Sc. (Data Science) Program is tailored for you.
The Online M.Sc.(Data Science) from VIT goes beyond simple analytics it offers a comprehensive curriculum that encompasses big data, machine learning, statistical modelling, business domain-analytics, and electives across diverse fields.
Learners will not only work with data, but interpret it, visualise it, and translate it into actionable strategy.
Delivered by VIT’s distinguished faculty with live sessions, recorded lectures, and flexible online access, this program allows you to study from anywhere and advance your career without relocation.
Approvals
VIT’s Online M.Sc.(Data Science) is backed by strong institutional credentials:
- UGC-entitled programme for online delivery.
- The university is accredited by the National Assessment and Accreditation Council (NAAC) with A++ grade.
- Recognised and ranked among top institutions in India (NIRF) and internationally.
These ensure that the degree you earn is valid for professional employment, higher studies, research roles, and global recognition.
Eligibility
To enrol in the VIT Online M.Sc.(Data Science) Program:
- A Bachelor’s degree in Engineering, Technology, Mathematics, Statistics, Computer Science or related discipline from a recognised university.
- Minimum aggregate marks as specified by VIT (for example 60% in many cases for full-time M.Sc programmes) though exact online criteria should be verified directly.
- Working professionals, fresh graduates, and candidates seeking a career shift are eligible.
- No entrance exam may be required for the online version (as per programme brochure).
Specializations & Course Fees
This program allows learners to explore advanced domains in data science and apply them in business, finance, healthcare, supply chain and more.
Available Focus Areas / Electives
- Big Data Analytics
- Machine Learning / Deep Learning
- Web & Social Media Analytics
- Financial Data Analytics
- Risk Analytics
- Supply Chain Analytics
- Natural Language Processing (NLP)
- Domain-based analytics (healthcare, marketing, etc)
Fee Structure
|
Category |
Semester-wise |
Year-wise |
Full Course Fee |
|
Domestic Students |
— |
— |
βΉ 1,70,000 approx (for 2 years) |
|
Additional Fees |
Application / exam fees |
— |
— |
|
Payment Options |
Online payments, instalments option indicated |
Admission Process
- Visit VIT Online or VIT University’s official online programme portal.
- Select “M.Sc.(Data Science) (Online)” programme.
- Fill the online application form with personal and academic details.
- Upload required documents (graduation marksheet, ID proof, photograph).
- Pay the programme/application fee through secure online gateway.
- After verification, receive admission confirmation along with online learning platform credentials.
The process is fully digital and designed to accommodate working professionals and remote learners.
Syllabus & Curriculum
The curriculum is structured over four semesters (2 years) and covers foundational, core, elective and project work.
|
Year |
Semester |
Core Subjects |
|
Year 1 |
Sem 1 |
Linear Algebra; Probability & Distribution Models; Exploratory Data Analysis; Data Structures & Algorithms; Python Programming |
|
Sem 2 |
Forecasting & Predictive Analytics; Statistical Inference; Database Management Systems; Data Mining; Artificial Intelligence |
|
|
Year 2 |
Sem 3 |
Elective I; Elective II; Elective III; Elective IV; Elective V |
|
Sem 4 |
Elective VI; Elective VII; Project / Dissertation |
Electives may include: Big Data Analytics, Deep Learning, NLP, Financial Analytics, Web & Social Media Analytics, Supply Chain Analytics, Risk Analytics.
Hands-on labs, research components, and industry-oriented assignments form part of the programme.
Placements
The online format does not guarantee placements, but VIT offers career support, alumni network access and industry-aligned curriculum favourable for job roles in analytics and data science.
|
Aspect |
Details |
|
Average Salary |
Data not publicly specified for online mode; full-time M.Sc in Data Science at VIT reports packages up to ~βΉ9.9 LPA for on-campus. |
|
Top Roles |
Data Scientist, Machine Learning Engineer, Business Intelligence Analyst, Data Engineer, Analytics Consultant |
|
Recruiters |
Tech companies, Financial Institutions, Healthcare Data firms, E-commerce, Consulting firms |
|
Higher Study Options |
PhD in Data Science/AI, Analytics consulting, Research Scientist roles |
Frequently Asked Questions
Yes , it is UGC-entitled and delivered by a reputed institution with proper accreditation.
While helpful, beginners with strong quantitative skills can enroll (as per brochure).
Yes , fully online, with flexibility for live + recorded sessions.
Typically a mix of online assessments, assignments, and project evaluation (confirm specifics from university).
Yes , final semester includes project work / dissertation.
Yes , instalment options are indicated by VIT for this programme.
Yes , the qualification supports admission to research programmes in data science, AI and analytics.
Electives span Big Data, ML, AI, Financial Analytics, NLP, Web/Social Media Analytics, Risk Analytics, etc.
Admission is merit-based; specific cut-off scores vary by session and applicant pool β consult the official portal.
Reviews highlight VITβs strong brand, flexible mode, industry-relevant curriculum, though exact placement data for online mode is less transparent.
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Updated Industry-Focused Curriculum:
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