Program Brochure
B.Sc. (Data Science)
The School of Data Science and CS & IT aims to persistently aspire to achieve excellence in computing disciplines. It is being followed in the computation of contemporary expectations across its range of academic programs.
Duration
3 Years
Students can download brochure to know more about the programme and apply for admissions 2026.
The main goal is to create future computer graduates, design and implement systems that include the convergence of software and hardware devices, employ creative approaches to programming and problem solving, create large-scale software systems, and build data/computing infrastructure for an organization.
The technology is new and the techniques of committing crimes are also new. It is no brainer that new approaches, practices, technology, and tools are also required to tackle such crimes from identification, prevention, and curation. The course design is intended to create skills within the students so that they can manage such circumstances efficiently and help the industry save billions of dollars.
Data Science is quite a popular field that has practical application in various domains including Academia, Business Sectors, R&D, and many more sectors which enables us to make effective decisions in day-to-day activities. B.Sc in Data Science course aims to provide an opportunity for all students to master the skill sets specific to Data Science with a research bent. The curriculum supports the students to obtain adequate knowledge in the theoretical aspects with hands-on experience in relevant domains and tools. Our students gain exposure to research models and industry-standard applications in Data Science through Guest Lectures, Seminars, Projects, Internships, GDs, and Industry activities.
The curriculum of BSc Data Science at SSPU aims to build a program that makes our students fully qualified, knowledgeable in Application Creation, Data Science, and Machine Learning.
Highlights of Program:
- Project-based learning through industry collaboration
- Focus on Skill building & Practical implementation
- Every Year Internship opportunity to gain relevant industry exposure
- The workshop, Guest Lectures, and interactive sessions with industry experts
Eligibility Criteria
- Passed 10+2 or an equivalent qualification in any stream with a minimum of 50% marks for the General (Open) category, and at least 45% marks for candidates belonging to Reserved Categories, EWS, and PWD from Maharashtra State only.
- The final Merit list shall be prepared on the basis of marks obtained by the candidate in the Personal Interview conducted by SSPU. Students from Non mathematical background must complete a bridge course in Mathematics & Statistics.
- A candidate who has completed 10+2 examination any stream or equivalent with minimum 50% from any Foreign Board must obtain an equivalent certificate from the Association of Indian Universities (AIU) (the application format is available on AIU website link:https://www.spuvvn.edu/orbit-cdn/uploads/2019/12/AIU_eveform.pdf
- All foreign qualifications need to be verified from Association of Indian Universities (AIU) by the candidate before seeking provisional admission.
- In order to promote international understanding between Indian and Foreign students, Scholastic Assessment test (SAT) scores are accepted
- Candidates will be selected based on their performance in the selection process as set by SSPU. Selected Students will be granted for provisional admission.
- The final Merit list shall be prepared on the basis of their performance in the selection process as set by SSPU.
- Eligibility Criteria for Indian Nationals:
Candidate having completed First Year BSc Data Science from any other recognized institute /university after credits mapping by the SSPU equivalence committee. (Internship 8 credits).
- Eligibility Criteria for NRI / International Students
Candidate having completed First Year BSc Data Science from any other recognized institute /university after credits mapping by SSPU equivalence committee.
Students must obtain an equivalent certificate from the Association of Indian Universities (AIU). All foreign qualifications need to be verified by Association of Indian Universities (AIU).
Fee Details
1st Year (New Admission)
| Caution Money | Academic Fees | NSDC Fees | Total Fees | 1st Installments | 2nd Installments |
|---|---|---|---|---|---|
| At the time of Admission | Due Date – 31-10-2026 | ||||
| ₹10,000 | ₹2,10,000 | ₹14,500 | ₹2,34,500 | ₹1,29,500 | ₹1,05,000 |
2nd Year Onwards (Existing Students)
| Academic Fees | 1st Installments | 2nd Installments |
|---|---|---|
| Due Date – 31-07-2026 | Due Date – 31-10-2026 | |
| ₹2,24,500 | ₹1,19,500 | ₹1,05,000 |
Hostel Charges
| 1 | 2 Seater Non-AC Rooms | 2,05,000 |
| 2 | Hostel Caution Money (Refundable) | 15,000 |
1st Year (New Admission)
| Caution Money | Academic Fees | NSDC Fees | Total Fees | 1st Installments | 2nd Installments |
|---|---|---|---|---|---|
| At the time of Admission | Due Date – 31-10-2026 | ||||
| ₹10,000 | ₹2,50,000 | ₹14,500 | ₹2,74,500 | ₹1,49,500 | ₹1,25,000 |
2nd Year Onwards (Existing Students)
| Academic Fees | 1st Installments | 2nd Installments |
| Due Date – 31-07-2026 | Due Date – 31-10-2026 | |
| ₹2,64,500 | ₹1,39,500 | ₹1,25,000 |
Hostel Charges
| 1 | 2 Seater Non-AC Rooms | 2,05,000 |
| 2 | Hostel Caution Money (Refundable) | 15,000 |
Note 1 : The University shall remit the NSDC Certification Fees to NSDC and Ethnotech
Note 2 : The academic fee may be increased up to 10% each year, as per the University policy and at the discretion of the Management.
Future Opportunities
Career opportunities include roles such as
Data Administrator
Data Analyst
Data Scientist
Developer
Machine Learning Engineer
Machine Learning Scientist
Applications Architect
Data Architect
Enterprise Architect
Statistician
Business Intelligence Analyst
Curriculum
| Course Code | Courses | Hours | Credits | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| L | T | P | S | Total | L | T | P | S | Total | ||
| DS101 | Basics of Data Science | 1 | 0 | 2 | 1 | 4 | 1 | 0 | 1 | 1 | 3 |
| DS102 | Introduction to C Programming | 2 | 0 | 2 | 1 | 5 | 2 | 0 | 1 | 1 | 4 |
| DS103 | Architecture and Operating System | 2 | 0 | 2 | 1 | 5 | 2 | 0 | 1 | 1 | 4 |
| DS104 | Linear Algebra and Basics of Calculus | 1 | 1 | 2 | 1 | 5 | 1 | 1 | 1 | 1 | 4 |
| DS105 | Data Analysis using Spread Sheet (VBA) | 2 | 0 | 2 | 1 | 5 | 2 | 0 | 1 | 1 | 4 |
| DS106 | Banking Part-I | 1 | 0 | 2 | 1 | 4 | 1 | 0 | 1 | 1 | 3 |
| IDSCUG02 | Career Development Skills | 0 | 0 | 0 | 2 | 2 | 0 | 0 | 0 | 2 | 2 |
| IDSC Open Elective | 0 | 0 | 0 | 2 | 2 | 0 | 0 | 0 | 2 | 2 | |
| Total Hours | 30 | Total Credits | 24 | ||||||||
| Course Code | Courses | Hours | Credits | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| L | T | P | S | Total | L | T | P | S | Total | ||
| DS201 | Probability & Statistics | 2 | 0 | 2 | 1 | 5 | 2 | 0 | 1 | 1 | 4 |
| DS202 | Data Structure and Algorithm | 2 | 0 | 2 | 1 | 5 | 2 | 0 | 1 | 1 | 4 |
| DS203 | Python Programming – I | 2 | 0 | 2 | 1 | 5 | 2 | 0 | 1 | 1 | 4 |
| DS204 | Database Management System (DBMS) with SQL | 2 | 0 | 2 | 1 | 5 | 2 | 0 | 1 | 1 | 4 |
| DS205 | R Programming | 2 | 0 | 2 | 1 | 5 | 2 | 0 | 1 | 1 | 4 |
| DS206 | Introduction to Business Domain-II | 1 | 0 | 2 | 1 | 4 | 1 | 0 | 1 | 1 | 3 |
| IDSCUG01 | Indian Knowledge System | 0 | 0 | 0 | 2 | 2 | 0 | 0 | 0 | 2 | 2 |
| DS207 | Internship | 0 | 0 | 16 | 0 | 16 | 0 | 0 | 0 | 8 | 8 |
| Total Hours | 31 | Total Credits | 33 | ||||||||
| IDSC Open Elective | 2 | 2 | |||||||||
| Course Code | Courses | Hours | Credits | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| L | T | P | S | Total | L | T | P | S | Total | ||
| DS301 | Python Programming-II | 2 | 0 | 2 | 1 | 5 | 2 | 0 | 1 | 1 | 4 |
| DS302 | Big Data Architecture and Ecosystem | 2 | 0 | 2 | 1 | 5 | 2 | 0 | 1 | 1 | 4 |
| DS303 | Machine Learning-I | 1 | 0 | 2 | 1 | 4 | 1 | 0 | 1 | 1 | 3 |
| DS304 | Core Java | 2 | 0 | 2 | 1 | 5 | 2 | 0 | 1 | 1 | 4 |
| DS305 | Data Mining and Data Warehousing | 2 | 0 | 2 | 1 | 5 | 2 | 0 | 1 | 1 | 4 |
| DS306 | Advanced Business Domain-I | 1 | 0 | 2 | 1 | 4 | 1 | 0 | 1 | 1 | 3 |
| IDSCUG04 | Career Progression Skills | 0 | 0 | 0 | 2 | 2 | 0 | 0 | 0 | 2 | 2 |
| Total Hours | 30 | Total Credits | 24 | ||||||||
| IDSC Open Elective | 0 | 0 | 0 | 2 | 2 | 0 | 0 | 0 | 2 | 2 | |
| Course Code | Courses | Hours | Credits | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| L | T | P | S | Total | L | T | P | S | Total | ||
| DS401 | Machine Learning-II | 1 | 0 | 2 | 1 | 4 | 1 | 0 | 1 | 1 | 3 |
| DS402 | Big Data Technologies using Hadoop | 2 | 0 | 2 | 1 | 5 | 2 | 0 | 1 | 1 | 4 |
| DS403 | Introduction to Power BI | 1 | 0 | 2 | 1 | 4 | 1 | 0 | 1 | 1 | 3 |
| DS404 | Introduction to Web Technology | 2 | 0 | 2 | 1 | 5 | 2 | 0 | 1 | 1 | 4 |
| DS405 | Introduction to Artificial Intelligence | 1 | 0 | 2 | 1 | 4 | 1 | 0 | 1 | 1 | 3 |
| DS406 | Advanced Business Domain-II | 1 | 0 | 2 | 1 | 4 | 1 | 0 | 1 | 1 | 3 |
| IDSCUG03 | Constitution of India | 0 | 0 | 0 | 2 | 2 | 0 | 0 | 0 | 2 | 2 |
| DS407 | INTERNSHIP | 0 | 0 | 16 | 0 | 16 | 0 | 0 | 0 | 0 | 8 |
| Total Hours | 28 | Total Credits | 30 | ||||||||
| IDSC Open Elective | 2 | 2 | |||||||||
| Course Code | Courses | Hours | Credits | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| L | T | P | S | Total | L | T | P | S | Total | ||
| DS501 | Apache Spark and Scala | 2 | 0 | 2 | 1 | 5 | 2 | 0 | 1 | 1 | 4 |
| DS502 | Data Visualization using Tools | 2 | 0 | 2 | 1 | 5 | 2 | 0 | 1 | 1 | 4 |
| DS503 | Data Security and Compliances | 2 | 0 | 2 | 1 | 5 | 2 | 0 | 1 | 1 | 4 |
| DS504 | Basics of Data Management using Cloud | 2 | 0 | 2 | 1 | 5 | 2 | 0 | 1 | 1 | 4 |
| DS505 | Introduction to Deep Learning | 1 | 0 | 2 | 1 | 4 | 1 | 0 | 1 | 1 | 3 |
| IDSCUG06 | Professional Ethics and Inclusive Practices | 0 | 0 | 0 | 3 | 2 | 0 | 0 | 0 | 3 | 2 |
| Total Hours | 26 | Total Credits | 21 | ||||||||
| IDSC Open Elective | 2 | 2 | |||||||||
| Course Code | Courses | Hours | Credits | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| L | T | P | S | Total | L | T | P | S | Total | ||
| IDSCUG05 | EVS and Sustainability | 0 | 0 | 0 | 2 | 2 | 0 | 0 | 0 | 2 | 2 |
| DS602 | Full Time Industrial Training / Internship / Project / Dissertation | 0 | 0 | 48 | 0 | 48 | 0 | 0 | 0 | 24 | 24 |
| Total Credits | 26 | ||||||||||
| IDSC Open Elective | 2 | 2 | |||||||||
Program Educational Objectives (PEOs)
PEO1
Demonstrate foundational knowledge in statistics, programming, and data analytics to solve real-world problems effectively.
PEO2
Acquire industry-relevant skills through hands-on training, internships, and projects using modern data science tools and platforms.
PEO3
Contribute to data-driven innovation, entrepreneurship, and sustainable development through creative problem-solving.
Program Specific Outcomes (PSOs)
01
Develop and deploy analytical models and algorithms using programming languages and frameworks.
02
Develop skills to design data driven solutions using visualization tools and techniques in the real world applications.
FAQs
The curriculum includes programming (Python/R), statistics, machine learning, data visualization, big data analytics, and artificial intelligence fundamentals.
The program focuses on a blend of academic excellence and practical skills, industry-oriented curriculum, and exposure to real-world data science applications.
Yes, internships are an integral part of the curriculum to provide real-world exposure and industry experience.
The program is a 3-year undergraduate course divided into six semesters, designed to provide both theoretical knowledge and practical skills.
Yes, graduates can opt for higher studies such as M.Sc Data Science, MBA (Analytics), or specialized certifications in AI and data science.
Graduates can pursue roles such as Data Analyst, Data Scientist, Business Analyst, Machine Learning Engineer, and AI Specialist.
Yes, SSPU provides strong industry connections, training, and placement assistance to help students secure job opportunities.
Yes, the program emphasizes skill-based learning through labs, live projects, internships, and industry collaborations.
Students gain hands-on experience with tools like Python, R, SQL, Tableau/Power BI, and various machine learning frameworks.
Programs at SSPU
Schools at SSPU
-
School of Architecture, Urban Development, Planning and Design
-
School of Retail Management
-
School of Interdisciplinary science
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School of Beauty & Wellness
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School of Computer Science and Information Technology
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School of Banking, Financial Services and Insurance Management
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School of Nutrition and Dietetics
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School of Data Science
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School of Construction Engineering and Infrastructure Management
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School of Energy and Sustainability Engineering
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School of Ports, Terminal Management & Logistics
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School of Mechatronics Engineering
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School of Media Management
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School of Defence & Aerospace Technology
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School of Automobile Engineering
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