Online M.Sc Data Science – SASTRA Deemed University
The Online Master of Science (M.Sc.) in Data Science from SASTRA Deemed University is a two-year, 80-credit postgraduate programme designed to equip learners with advanced expertise in data science, machine learning, statistical analysis, and big data technologies. SASTRA is ranked #29 among Indian universities in NIRF 2025, holds NAAC 'A++' re-accreditation (fourth cycle), and is classified as a Category I Institution by the UGC — making this online degree equivalent in recognition to a traditional campus-based M.Sc. The curriculum spans four semesters and covers probability and statistics, Python for data science, artificial intelligence, machine learning, deep learning, predictive analytics, RDBMS and SQL, data mining, machine vision, and ethics and data security. Elective modules in Semesters 3 and 4 allow specialisation across domains including financial data analysis, healthcare analytics, NLP, image processing, spatial data analytics, and more. Eligibility requires a bachelor's degree in any discipline with a background in mathematics or statistics. Graduates are prepared for high-demand roles such as data scientist, machine learning engineer, data analyst, business intelligence analyst, AI research scientist, and data architect. The programme accommodates working professionals with self-paced e-tutorials, downloadable materials, and live webinars accessible via LMS.
21,000 already enrolled
English
Not specified
Course Start Date:
14th May, 2026
Application Deadline:
Closing Soon
Duration:
2 Years
₹ 1,60,000 - 2,40,000
Overview
SASTRA Deemed University's Online M.Sc in Data Science is a two-year, 80-credit postgraduate programme combining rigorous academic foundations with hands-on data science practice. The programme is UGC-recognised, offered by a NAAC A++ accredited institution ranked #29 in NIRF 2025, and holds the same academic value as a traditional on-campus M.Sc degree. Structured across four semesters of 20 credits each, the curriculum covers the full data science stack — from probability, statistics, and mathematics through Python, AI, machine learning, deep learning, predictive analytics, RDBMS, data mining, and machine vision — with domain electives available from Semester 3. Learners can specialise in areas such as financial data analysis, healthcare analytics, NLP, spatial data analytics, image processing, and more. The programme's flexible online delivery, with self-paced tutorials, downloadable content, and live webinars, makes it suitable for both recent graduates and working professionals across India and globally.
Why Master of Science (MSc)?
This programme offers the credibility of a NAAC A++, NIRF Rank 29 university degree in one of the most in-demand disciplines globally, at an affordable fee structure with loan facilities available. The curriculum is comprehensive and modern, covering not just core data science but also emerging areas like deep learning, machine vision, and domain-specific analytics. Practical learning is central — real-world projects and case studies build a professional portfolio that graduates can use directly in job applications. The elective system in Semesters 3 and 4 offers genuine flexibility, allowing learners to align their specialisation with their target industry. Career support through job fairs, placement services, and alumni networks further strengthens post-programme employability, while SASTRA's strong corporate brand recognition opens doors in India's leading technology and analytics firms.
What does this course have to offer?
Key Highlights
UGC-recognised online M.Sc degree equivalent to traditional campus qualification
NIRF 2025 Rank #29 among Indian universities
NAAC A++ accredited institution
80 credits across 4 semesters with 20 courses
Python, R, SQL, machine learning, deep learning, and big data in the core curriculum
Domain electives across healthcare, finance, NLP, spatial analytics, and more
Hands-on projects and real-world case studies
Flexible learning via e-tutorials, webinars, and LMS available 24/7
Loan facility and multiple payment options available
Limited-time discounted fee of Rs 1,60,000 for July 2026 batch
Interested in career outcomes and specializations?
Who is this programme for?
Recent graduates with a bachelor's degree and a background in mathematics or statistics seeking a postgraduate data science qualification
Working professionals in technology, finance, or analytics looking to specialise or upskill in data science
Individuals targeting careers as data scientists, ML engineers, data analysts, or AI researchers
Learners seeking a recognised, affordable online M.Sc from a top-ranked Indian university
Minimum Eligibility
Graduate or bachelor's degree (10+2+3 or 10+2+4) or equivalent from any recognised university
Background in Mathematics or Statistics is required
Open to students from India and abroad
No minimum work experience required
Not sure whether you qualify for this programme?
Who is the programme for?
Applicants must hold a graduate or bachelor's degree (10+2+3 or 10+2+4 pattern) or equivalent in any discipline from a recognised university, with a background in Mathematics or Statistics. No minimum work experience is required. The programme is open to learners from India and internationally. Applications are submitted online, with free admission counselling available. The academic structure spans four semesters over two years, totalling 80 credits across 20 courses. Domain electives are chosen in Semesters 3 and 4 from a pool covering financial analytics, healthcare data science, NLP, image processing, spatial analytics, and more. Assessment consists of MCQ and descriptive evaluations conducted periodically; students must complete all assessment components and meet attendance criteria to receive the degree certificate. A final-semester project and viva voce carries 8 credits.
Selection process
How to apply?
Curriculum
The curriculum is structured across four semesters totalling 80 credits and 20 courses. Semester 1 establishes mathematical and statistical foundations alongside Python for data science and artificial intelligence. Semester 2 moves into machine learning, big data mining, SQL and visualisation, data mining techniques, and research methodology. Semester 3 introduces deep learning, predictive analytics, ethics and data security, and two domain electives. Semester 4 covers machine vision, two further electives, and an 8-credit project with viva voce. The elective pool spans 13 specialisation areas including algorithmic trading, Bayesian data analysis, financial data analysis, healthcare analytics, NLP, image processing, spatial data analytics, speech and video processing, and energy systems modelling, allowing learners to tailor the degree to their target industry.
There are 4 semesters in this course
Semester 1 focuses on quantitative and programming foundations, covering Probability and Statistics using R, Mathematics for Data Science, Python for Data Science, Artificial Intelligence and Reasoning, and Applied Multivariate Analysis, totalling 20 credits. Semester 2 deepens applied machine learning and data management skills through Machine Learning, Big Data Mining and Analytics, RDBMS and SQL and Visualisation, Data Mining Techniques, an RDBMS and SQL Laboratory, and Research Methodology and IPR, totalling 20 credits. Semester 3 advances into cutting-edge techniques with Deep Learning and Applications, Predictive Analytics Regression and Classification, Ethics and Data Security, and two elective papers from a broad domain pool, totalling 20 credits. Semester 4 completes the programme with Machine Vision, two further elective papers, and an 8-credit Project Work and Viva Voce that integrates learning from all four semesters into a real-world data science deliverable, totalling 20 credits. Elective topics span algorithmic trading, Bayesian data analysis, financial data analysis, healthcare data analytics, data science for structural biology, epidemiological modelling, social networks and graph analysis, spatial data analytics, information visualisation, image processing, speech and video processing, information retrieval and NLP, and energy systems modelling.
Semester 1
Semester 2
Semester 3
Semester 4
Programme Length
2 years (4 semesters, 80 credits, 20 courses)
Tuition Fee
The standard programme fee is Rs 60,000 per semester, totalling Rs 2,40,000 for the full two-year programme. A limited-time early bird discounted fee of Rs 1,60,000 is available. An annual payment option of Rs 90,000 per year is also offered. Students may also make a down payment of Rs 20,000 and avail loan or financial assistance for the remaining balance at attractive rates. All payment options support both upfront and instalment-based settlement to accommodate learners' financial situations.
Fee Structure
Payment options
Financing options
Need help understanding fees, EMI options, or scholarships?
Learning Experience
The programme is delivered entirely online through a four-component learning model. E-tutorials are pre-recorded expert video lessons uploaded weekly for 12 weeks per semester, accessible until semester completion, enabling asynchronous self-paced study. E-content includes e-books, lecture notes, PPTs, and open-source materials made available from day one and downloadable across all devices at any time. Webinars are live synchronous sessions requiring students to have studied the preceding three weeks of content, fostering interactive real-time engagement with faculty. Assessments are conducted periodically using MCQ and descriptive formats to ensure ongoing knowledge consolidation. All study materials, including e-tutorials, lecture notes, and webinars, are accessible 24/7 via the LMS, making the programme equally suitable for full-time students and working professionals.
University Experience
SASTRA Deemed University is one of India's leading research and teaching institutions, ranked #29 among universities in NIRF 2025 and re-accredited by NAAC with an 'A++' grade in its fourth cycle. It is classified as a Category I Institution by the UGC and recognised as a Scientific and Industrial Research Organisation by the Government of India. Twelve of SASTRA's engineering programmes hold nine-year international accreditation from the IET, UK. The university's strong industry reputation, experienced faculty with active research profiles, and project-based curriculum ensure that an online degree from SASTRA carries genuine employer recognition. Learners benefit from a well-established academic community and career support infrastructure including job fairs and placement assistance.
Loading alumni...
About the University
Established in 1984, SASTRA is a premier private deemed university located in Thanjavur, Tamil Nadu. The university operates across multiple campuses offering comprehensive education through various schools including Engineering, Medicine, Management, Law, Sciences, and Humanities. With a strong focus on research and innovation, SASTRA has emerged as one of India's leading institutions, known for its academic excellence and industry-aligned curriculum.
#801-850
QS World Ranking 2025
#22
NIRF University Rank 2024
3200+
Faculty Staff
Affiliation & Recognition
UGC
NAAC
NBA
Institution of Engineering & Technology (IET), UK
Career services
SASTRA provides comprehensive career support through structured training programs and industry interactions. The center facilitates continuous institute-industry engagement through pre-placement training, industrial exhibitions, and seminars. Students receive intensive coaching in personality development, leadership qualities, and technical skills. The CDC organizes year-round placement activities including pre-placement talks, aptitude tests, group discussions, and interviews. The university mandates industrial training and internships, enabling students to gain practical industry exposure.
52 LPA
Highest Package 2024
980+
Total Recruiters 2024
94%
Placement Rate
Top Recruiters
Course Start Date:
14th May, 2026
Application Deadline:
Closing Soon
Duration:
2 Years
₹ 1,60,000 - 2,40,000
Frequently asked questions
Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.