Bachelor of Science (B.S.) in Data Science & Artificial Intelligence
Bachelor of Science (B.S.) in Data Science & Artificial Intelligence
As we stand at the forefront of the Fourth Industrial Revolution, data and intelligent systems are reshaping every sector from healthcare and finance to education and governance. Bachelor of Science (B.S.) in Data Science and Artificial Intelligence Programme is a timely response to the global demand for skilled professionals who can harness the power of Data and Artificial Intelligence to solve complex real-world problems.
This Programme is a Four-Year fully residential Program, a program crafted to meet the evolving needs of the digital era and nurture the next generation of data-driven innovators. Today, Data Science and Artificial Intelligence are not just tools they are transformative forces reshaping industries, economies, and societies. This is designed to provide students with a strong foundation in mathematics, statistics, computer science, and management while also equipping them with hands-on experience in machine learning, data engineering, AI, and real-world industry applications.
The B.S. in Data Science and Artificial Intelligence Programme at IIM Sambalpur offers a well-structured, four-year curriculum aligned with global academic and industry standards. The curriculum begins with foundational training in programming, mathematics, and statistics, then advances to core subjects such as machine learning, data mining, AI applications, big data technologies as well as core management courses. It culminates with specialized electives, capstone projects, and internships, enabling students to gain practical experience and domain-specific knowledge. This comprehensive framework ensures a balanced mix of theoretical learning, hands-on practice, and interdisciplinary exposure.
Program Objectives
- Develop core competencies in Data Science & Artificial Intelligence.
- Foster critical thinking and problem-solving abilities through hands-on experience with real-world datasets and Artificial Intelligence models.
- Cultivate analytical thinking to transform raw data into predictive insights for business, scientific, or societal applications.
- Bridge theory and practice by integrating academic knowledge with industry-relevant tools based on Data Science & Artificial Intelligence.
- Encourage innovation and research through interdisciplinary projects, capstone experiences, and exposure to emerging trends.
- Prepare graduates for diverse career paths in data science, artificial intelligence, business analytics and higher education or research.
Key Highlights
- Curriculum aligned with the latest industry trends and academic research frontiers.
- Intensive lab sessions, coding bootcamps, and case study-based teaching.
- Real-world exposure through live projects, internships, and industry collaborations.
- Final year dissertation focused on solving real-world problems using AI and data-driven approaches.
- Industry-focused modules co-designed with leading tech firms and AI practitioners.
- Multiple exit options in line with NEP: Certificate (1st Year), Diploma (2nd Year), Degree (3rd Year), Honours (4th Year)
Curriculum Overview
Programme Duration: 4 Years (8 Semesters) Total Credits: 170 The curriculum blends core knowledge in data science and AI with hands-on application, interdisciplinary learning, and industry exposure.Year 1: Semester-I
| Sl. No | Course Category | Course Name | Credits |
|---|---|---|---|
| 1 | Foundation | Statistics-I | 4.5 |
| 2 | Foundation | Mathematics I | 4.5 |
| 3 | Foundation | Programming Language-I | 3 |
| 4 | Management | Philosophy & Sociology | 4.5 |
| 5 | Management | Oral Communication | 3 |
| 6 | Management | Yoga & Positive Psychology | 3 |
| Total | 22.5 | ||
| Non-Credit course: Workshop/Certification | |||
Year 1: Semester-II
| Sl. No | Course Category | Course Name | Credits |
|---|---|---|---|
| 1 | Foundation | Statistics II | 3 |
| 2 | Foundation | Mathematics II | 3 |
| 3 | Foundation | Programming Language-II | 3 |
| 4 | Foundation | Data Visualization | 3 |
| 5 | Management | Principles of Economics | 4.5 |
| 6 | Management | Principles of Management | 3 |
| 7 | Management | Written Communication | 3 |
| Total | 22.5 | ||
| Non-Credit course: Workshop/Certification | |||
Year 2: Semester-III
| Sl. No | Course Category | Course Name | Credits |
|---|---|---|---|
| 1 | Foundation | Data Science: An Introduction | 4.5 |
| 2 | Foundation | Algorithm Design and Analysis | 3 |
| 3 | Foundation | Database Management Systems | 3 |
| 4 | Foundation | Data Structures | 3 |
| 5 | Foundation | Programming Language-III | 3 |
| 6 | Foundation | Introduction to AI | 3 |
| 7 | Management | Principles of Marketing | 3 |
| Total | 22.5 | ||
| Non-Credit course: Workshop/Certification | |||
Year 2: Semester-IV
| Sl. No | Course Category | Course Name | Credits |
|---|---|---|---|
| 1 | Foundation | Econometrics | 3 |
| 2 | Foundation | Machine Learning Fundamentals | 3 |
| 3 | Foundation | Introduction to Simulation | 3 |
| 4 | Foundation | Introduction to R | 3 |
| 5 | Management | Decision Modelling | 3 |
| 6 | Management | Foundations of Information Systems | 3 |
| 7 | Management | Financial Accounting and Financial Management | 4.5 |
| Total | 22.5 | ||
| Non-Credit course: Workshop/Certification | |||
Year 3: Semester-V
| Sl.No | Course Category | Course Name | Credits |
|---|---|---|---|
| 1 | Foundation | Data Mining and Warehousing | 4.5 |
| 2 | Foundation | Natural Language Processing | 3 |
| 3 | Foundation | Cloud Computing | 3 |
| 4 | Foundation | AI Tools and Applications | 3 |
| 5 | Management | Operations and Supply Chain Management | 3 |
| 6 | Management | Strategic Management | 3 |
| 7 | Management | Business Research Methods | 3 |
| Total | 22.5 | ||
| Non-Credit course: Workshop/Certification | |||
Year 3: Semester-VI
| Sl.No | Course Category | Course Name | Credits |
|---|---|---|---|
| 1 | Foundation | Deep Learning and Neural Networks | 4.5 |
| 2 | Foundation | Fundamentals of Blockchain | 3 |
| 3 | Foundation | Web Technologies | 3 |
| 4 | Foundation | Introduction to Cyber Security | 3 |
| 5 | Foundation | Quantum Computing | 3 |
| 6 | Foundation | Essentials of Generative AI, Prompt Engineering & ChatGPT | 3 |
| 7 | Management | Human Resource Management | 3 |
| Total | 22.5 | ||
| Non-Credit course: Summer Industry Internship | |||
Year 4: Research (Semester-VII)
| Sl.No | Course Category | Course Name | Credits |
|---|---|---|---|
| 1 | Research (Compulsory) | Marketing Research & Analytics | 4.5 |
| Any 5 Courses (Tentative List) | |||
| 2 | Research | Operations Analytics | 3 |
| 3 | Research | Big Data Analytics | 3 |
| 4 | Research | Advanced Generative AI | 3 |
| 5 | Research | Augmented and Virtual Reality | 3 |
| 6 | Research | Data Preprocessing & Feature Engineering | 3 |
| 7 | Research | Banking and Financial Service | 3 |
| 8 | Research | HR Analytics | 3 |
| 9 | Research | Supply Chain Analytics | 3 |
| 10 | Research | Revenue & Pricing Analytics | 3 |
| 11 | Research | AI Strategy, Ethics and Governance | 3 |
| 12 | Research | Fintech | 3 |
| 13 | Research | Emerging Technology in Human Resource Management | 3 |
| 14 | Research | Advanced Econometrics | 3 |
| 15 | Research | Security Analysis & Portfolio Management | 3 |
| 16 | Research | Strategy in the era of Big Data | 3 |
| 17 | Research | Emerging trends of Analytics and AI in Public Policy | 3 |
| Total | 19.5 | ||
Year 4: Research (Semester-VIII)
| Sl.No | Course Category | Course Name | Credits |
|---|---|---|---|
| 1 | Research | Dissertation | 15.5 |
| Total | 15.5 | ||
Exit Options Available After Each Year
| Year | Exit Option | Award |
|---|---|---|
| 1 | Certificate | Certificate |
| 2 | Diploma | Diploma |
| 3 | Degree | B.S. Degree |
| 4 | Honours | B.S. (Hons.) |
(a) Eligibility Criteria
Qualification
- Must have either passed their Class 12th examination in the year 2024 or 2025, or be currently appearing for Class 12th examination, with results expected by May/June 2025.
- Must have scored a minimum of 70% aggregate marks in both Class 10th and Class 12th from a recognized Board/University.
- Must have passed English language examination in 10th and 12th Class.
- Must have a valid IIT JEE (Mains) 2025 score (mandatory for all applicants).
Relaxation for Reserved Categories
- Reserved Categories (EWS, SC, ST, OBC-NCL, PwD):
- A 5% relaxation in Class 10th and Class 12th aggregate percentage will be provided.
- Reservation of seats will be as per Government of India’s reservation norms.
Age Limit
The maximum age for admission is 21 years as on July 31, 2025. However, relaxation in age will be provided as per Govt of India norms for the reserved candidates.(b) Admission Process
Stage 1: Application & Eligibility
Candidates will be required to submit their applications online through the IIM Sambalpur’s admission portal. All relevant and valid documents must be submitted at the time of application through online portal.Stage 2: Merit List Preparation
The final merit list will be prepared based on the IIT JEE (Main) Score.Reservation Policy
IIM Sambalpur will follow the reservation policy as per the Government of India regulations:- 15% of the seats are reserved for Scheduled Caste (SC) candidates.
- 7.5% of the seats are reserved for Scheduled Tribe (ST) candidates.
- 27% of the seats are reserved for Other Backward Classes – Non-Creamy Layer (OBC-NCL) candidates.
- 10% of the seats are reserved for Economically Weaker Sections (EWS) candidates.
- 5% of the seats are reserved for Persons with Disabilities (PwD).
Important Dates (Tentative)
- Application Start: June 15, 2025
- Last date of submission of online application: July 30, 2025
- Publication of Result : Tentatively August 18, 2025
- Programme Commencement: September 2025
Application Fee
- General Category: ₹1000 + Taxes (If any applicable)
- SC/ST/PwD Category/OBC-NCL /EWS: ₹500 + Taxes (If any applicable)
- The application fee is non-refundable.
- Applicants must pay the application fee (as applicable) through the online admission application portal.
Admission Confirmation
- Selected candidates will receive a provisional admission offer through email.
- To confirm their admission, candidates must pay the first instalment of the program fee within the stipulated deadline.
- Failure to pay the fee by the deadline will result in forfeiture of the offer and the extension of the offer to the next eligible candidate on the merit list.
Fee Structure for B.S. in Data Science & AI Program
| Year | Fall Semester | Spring Semester | Total |
|---|---|---|---|
| First Year | 3,71,500 | 3,31,500 | 7,03,000 |
| Second Year | 3,31,500 | 3,31,500 | 6,63,000 |
| Third Year | 3,31,500 | 3,36,500 | 6,68,000 |
| Fourth Year | 3,31,500 | 2,31,500 | 5,63,000 |
- The offer acceptance fee of Rs.50,000 will be adjusted against the SEM-I course fee.
- Each Semester fee includes Rs. 31,500/- Mess Deposit amount and this amount is subject to vary depending on the service provider’s charges.
- Semester 1 Fee includes an amount of Rs 40,000/- refundable caution money to be refunded at the end of the Programme, after adjusting the dues (if any).
- Semester 6 fee includes alumni fund contribution.
IIM Sambalpur reserves the right to modify any part of the admission policy and rules including the various criteria and cut offs mentioned at any time till the actual admission process for the batch is completed. Any dispute concerning Admission for the B.S. in Data Science & Artificial Intelligence Programme batch would be subject to jurisdiction of the competent courts within the territorial jurisdiction of city of Sambalpur only.
Contact Us
| B.S. Programme Office
IIM Sambalpur Basantpur Sambalpur-768025 (Odisha) |
Email for admission-related queries:
bs.admissions@iimsambalpur.ac.in Call: +91 9078455248 / +91 7327014789 WhatsApp: +91 7327014789 Office Email: office.bsds@iimsambalpur.ac.in |