B.Sc. – Artificial Intelligence and Data Science
Explore the language of intelligence, turn raw data into discovery, and engineer the algorithms of tomorrow with our B.Sc. in Artificial Intelligence and Data Science program at Indira University.
Study Mode
Full Time
Duration
Graduation - 3 Years & Honours -4 Years
Commencement
July 2026
Assessment
Semester
Location
School of Information Technology, Indira University, Tathawade , Pune
Overview
The B.Sc. in Artificial Intelligence and Data Science program is a cutting-edge undergraduate program designed to equip students with the artificial intelligence and data science skills needed to thrive in the era of intelligent systems and big data. The program integrates computer science, mathematics, statistics, and domain knowledge to build expertise in machine learning, deep learning, data analytics, and artificial intelligence. Students learn to collect, process, and analyze large volumes of data to develop data-driven insights and intelligent solutions.
The curriculum emphasizes practical learning through hands-on projects, industry internships, and exposure to real-world applications such as natural language processing, computer vision, and predictive modeling. Graduates are prepared for diverse career roles like Data Scientist, AI Engineer, Business Analyst, and Machine Learning Engineer across industries such as IT, finance, healthcare, and research. This innovation, problem-solving, and ethical AI practices shape Indira as the best college for B.Sc. in AI and Data Science in Pune.
AI and Data Science program at our university fosters innovation, problem-solving, and ethical AI practices, shaping students into future-ready professionals in the digital age.
Why pursue a B.Sc. in AI and Data Science program with Indira University?
Testimonials
Overview
The B.Sc. in Artificial Intelligence and Data Science syllabus is a journey that begins with cutting-edge learning, immersing you in the dynamic worlds of artificial intelligence, machine learning, and big data technologies. Through practical mastery, you will engage in real-world projects and hands-on coding, transforming theoretical knowledge into meaningful solutions. The close industry connect amplifies this experience: internships and expert-led sessions bring workplace insights directly into the classroom, bridging the gap between campus and career.
Innovation and research lie at the heart of the program, AI and Data Science, offering you the chance to explore creative AI applications that will shape tomorrow’s landscape. Equally important is the ethical edge you will develop, learning to design responsible and impactful AI systems. By the time you graduate, you will be career-ready and equipped not only with strong technical and analytical abilities but also with clear communication skills and leadership potential to excel in the evolving domain of intelligent systems and data innovation.

Curriculum
| SEMESTER I | ||
|---|---|---|
| Nature of the Course | Title | Credits |
| Major Mandatory | Problem Solving using Python Programming | 2 |
| Major Mandatory | Lab Course based on Python Programming | 2 |
| Major Mandatory | Descriptive Statistics | 2 |
| Major Mandatory | Lab Course based on Descriptive Statistics | 2 |
| Minor | Computational Mathematics | 2 |
| Minor | Lab Course based on Computational Mathematics | 2 |
| Open Elective | Digital Marketing | 2 |
| Skill Enhancement Course |
Foundations of AI and Data Science | 2 |
| Indian Knowledge System (Generic) |
Introduction to Indian Knowledge Systems (IKS) | 2 |
| Ability Enhancement Course |
English Proficiency Skills -I | 2 |
| Value Education Course |
Essentials of Sustainability | 2 |
| SEMESTER-II | ||
|---|---|---|
| Nature of the Course | Credits | Title |
| Major Mandatory | 2 | Advanced Python Programming |
| Major Mandatory | 2 | Lab Course on Advanced Python |
| Major Mandatory | 2 | Probability & Distributions |
| Major Mandatory | 2 | Graph Theory |
| Minor | 2 | Database Management System |
| Minor | 2 | Lab Course on Database Management System |
| Open Elective | 2 | Foreign Language-II (German/Korean/Spanish) |
| Skill Enhance Course | 2 | Lab Course based on Probability and Graph Theory |
| Ability Enhancement Course | 2 | English Proficiency Skills – II |
| Value Education Course | 1 | Environmental Studies |
| Value Education Course | 1 | Decoding AI |
| Co-curricular Course | 2 | Health & Wellness, Yoga Education, Sports & Fitness, Cultural Activities, NSS/NCC and Fine/Applied/Visual/Performing Arts |
| Semester III | ||
|---|---|---|
| Nature of the Course | Credits | Title |
| Major Mandatory | 2 | Relational Database Management System |
| Major Mandatory | 2 | Basic Data Structures |
| Major Mandatory | 2 | Lab Course on RDBMS |
| Major Mandatory | 2 | Computing in Ancient India |
| Vocational Skill Course | 2 | Lab Course on Data Structures |
| Minor | 2 | Inferential Statistics |
| Minor | 2 | Lab Course on Inferential Statistics |
| Open Elective | 2 | Foreign Language-III (German / Korean / Spanish) |
| Ability Enhancement Course | 2 | Modern Indian Languages (Hindi / Marathi / Sanskrit) |
| Field Project | 2 | Mini Project |
| Co-curricular Course | 2 | Physical Education + SOUL |
| Semester IV | ||
|---|---|---|
| Nature of the Course | Credits | Title |
| Major Mandatory | 2 | Supervised Machine Learning Techniques |
| Major Mandatory | 2 | Advanced Data Structures |
| Major Mandatory | 2 | Lab Course on Supervised ML and Advanced Data Structures |
| Major Mandatory | 2 | Core Artificial Intelligence Concepts |
| Major Mandatory | 2 | Lab Course on Core Artificial Intelligence |
| Vocational Skill Course | 2 | Linear Algebra for Machine Learning |
| Open Elective | 2 | Foreign Language-IV (German / Korean / Spanish) |
| Skill Enhancement Course | 2 | Software Engineering |
| Ability Enhancement Course | 2 | Modern Indian Languages (Hindi / Marathi / Sanskrit) |
| Field Project | 2 | Mini Project |
| Co-curricular Course | 2 | Health & Wellness, Yoga Education, Sports & Fitness, Cultural Activities, NSS/NCC and Fine/Applied/Visual/Performing Arts/Physical Education |
| Semester V | ||
|---|---|---|
| Nature of the Course | Credits | Title |
| Major Mandatory | 2 | Advanced AI Techniques & Applications |
| Major Mandatory | 2 | Unsupervised Machine Learning Techniques |
| Major Mandatory | 2 | DAA – I (Brute Force, D&C, Greedy, Dynamic Programming) |
| Major Mandatory | 2 | Lab Course on Advanced Artificial Intelligence |
| Major Mandatory | 2 | Lab Course on Unsupervised Machine Learning |
| Minor | 2 | Operations Research |
| Major Elective | 2 | MEAN (MongoDB, Express.js, AngularJS, Node.js) |
| Major Elective | 2 | Practical based on MEAN |
| OR | ||
| Major Elective | 2 | Mobile Application Development |
| Major Elective | 2 | Lab Course based on Mobile Application Development |
| Vocational Skill Course | 2 | Lab Course on Power BI & Tableau |
| Field Project | 4 | Project Work |
| Semester VI | ||
|---|---|---|
| Nature of the Course | Credits | Title |
| Major Mandatory | 2 | Data Preparation and Visualization |
| Major Mandatory | 2 | Data Mining and Warehousing |
| Major Mandatory | 2 | DAA – II (Backtracking, B&B, Randomized, P&NP and Approximation Algorithms) |
| Major Mandatory | 2 | Lab Course on Data Preparation and Visualization |
| Major Mandatory | 2 | Lab Course on Data Mining and Warehousing |
| Major Elective | 2 | Big Data Analytics |
| Major Elective | 2 | Lab Course on Big Data Analytics |
| OR | ||
| Major Elective | 2 | Financial Analytics |
| Major Elective | 2 | Lab Course on Financial Analytics |
| Minor | 2 | NoSQL Databases |
| On Job Training | 4 | On Job Training |
| Semester VII (Honors with Research Degree) | ||
|---|---|---|
| Nature of the Course | Credits | Title |
| Major Mandatory | 4 | Deep Learning – I |
| Major Mandatory | 2 | Natural Language Processing – I |
| Major Mandatory | 2 | Lab Course on Deep Learning |
| Major Mandatory | 2 | Lab Course on Natural Language Processing |
| Major Elective | 2 | Supply Chain & Logistics Analytics |
| Major Elective | 2 | Lab Course on Supply Chain & Logistics Analytics |
| OR | ||
| Major Elective | 2 | Healthcare Analytics |
| Major Elective | 2 | Lab Course on Healthcare Analytics |
| Research Project | 4 | Research Project |
| Research Methodology | 4 | Research Methodology |
| Semester VII (Honors Degree) | ||
|---|---|---|
| Nature of the Course | Credits | Title |
| Major Mandatory | 2 | Deep Learning – I |
| Major Mandatory | 2 | Natural Language Processing – I |
| Major Mandatory | 2 | Lab Course on Deep Learning |
| Major Mandatory | 2 | Lab Course on Natural Language Processing |
| Major Mandatory | 2 | Cloud Computing |
| Major Elective | 2 | Supply Chain & Logistics Analytics |
| Major Elective | 2 | Lab Course on Supply Chain & Logistics Analytics |
| OR | ||
| Major Elective | 2 | Healthcare Analytics |
| Major Elective | 2 | Lab Course on Healthcare Analytics |
| Research Methodology | 4 | Research Methodology |
| Semester VIII (Honors with Research Degree) | ||
|---|---|---|
| Nature of the Course | Credits | Title |
| Major Mandatory | 4 | Deep Learning – II |
| Major Mandatory | 2 | Natural Language Processing – II |
| Major Mandatory | 2 | Lab Course on Deep Learning |
| Major Mandatory | 2 | Lab Course on Natural Language Processing |
| Major Elective | 2 | DevOps |
| Major Elective | 2 | Lab Course Based on DevOps |
| OR | ||
| Major Elective | 2 | Computer Vision (Image Processing) |
| Major Elective | 2 | Lab Course on Computer Vision |
| Research Project | 8 | Research Project |
| Semester VIII (Honors Degree) | ||
|---|---|---|
| Nature of the Course | Credits | Title |
| Major Mandatory | 4 | Deep Learning – II |
| Major Mandatory | 2 | Natural Language Processing – II |
| Major Mandatory | 2 | Lab Course on Deep Learning |
| Major Mandatory | 2 | Lab Course on Natural Language Processing |
| Major Mandatory | 4 | Natural Language Processing |
| Major Elective | 2 | DevOps |
| Major Elective | 2 | Lab Course Based on DevOps |
| OR | ||
| Major Elective | 2 | C# .NET Programming |
| Major Elective | 2 | Lab Course on C# .NET |
| On Job Training | 4 | On Job Training |
Pedagogy and Learning Methodology
The bachelor’s in artificial intelligence and data science program employs a hands-on, experiential pedagogy aimed at providing students with foundational exposure to data and its applications. Learners engage in interactive lectures, practical labs, and beginner-level projects to understand core concepts in data analytics, programming, and AI tools. Through structured exercises and case studies, students develop analytical thinking, problem-solving, and basic data-handling skills. Collaborative assignments, workshops, and mentorship sessions foster teamwork and communication. The curriculum emphasizes ethical use of data, computational thinking, and iterative learning. By blending theory with practice, students gain confidence in exploring datasets, experimenting with AI models, and building a strong foundation for advanced studies and real-world applications in data science.
Key Points:
- Foundational Exposure
- Interactive Lectures
- Practical Labs
- Collaborative Assignments
- Case Studies and Workshops
- Mentorship Sessions
Industry Immersion
Industry immersion introduces undergraduate students to real-world AI and Data Science applications through Case Study-based problem solving, micro internships in collaborations with tech companies. Students gain practical experience in data analytics, machine learning, and AI solutions, bridging academic concepts with industry practices to build strong professional skills and a career readiness skill set.
Exposure Trips
At our university, we believe learning goes beyond classrooms. The Exposure Trips for the course are designed to immerse students in real-world environments where cutting-edge technologies are shaping the future. These trips include visits to leading IT companies, AI research labs, data analytics firms, and innovation hubs, offering students a chance to observe live projects and interact with industry experts. Students gain insights into AI applications, big data workflows, cloud platforms, and emerging trends. Through these experiences, learners develop practical skills, networking opportunities, and industry readiness, ensuring they graduate with both academic knowledge and hands-on exposure.
Career Opportunities
A bachelor’s degree in artificial intelligence and data science equips students with foundational skills in programming, machine learning, and data analytics, preparing them for a wide range of entry-level and evolving career opportunities. Graduates can pursue roles such as Data Analyst, Machine Learning Assistant, AI Developer, Business Intelligence Associate, and Data Engineer Trainee. With the future of technology increasingly driven by AI and data-based solutions, this program offers strong career prospects in industries like IT, finance, healthcare, and education. Students can also explore roles in AI testing, data visualization, and research assistance, building a solid base for advanced studies or specialization.
The career opportunities for the students of artificial intelligence and data science include:
Data Analyst
Machine Learning Engineer
AI Developer / Assistant AI Engineer
Data Engineer Trainee
Business Intelligence (BI) Associate
Data Scientist
AI Research Assistant
Natural Language Processing (NLP) Intern / Assistant
Computer Vision Developer (Entry-Level)
Robotics Programmer (Junior Level)
Data Visualization Specialist
AI Testing and Validation Engineer
Data Science Intern / Associate
AI Solutions Associate
AI Ethics and Compliance Assistant
Overview
The B.Sc. in AI & DS admission process at Indira University is designed to be straightforward and transparent. Each stage, from filling out the application form to final submission, is clearly outlined, providing applicants with a seamless and hassle-free experience as they apply to various programs.
HSC (10+2) Science Stream with Mathematics or its equivalent Examination.
Or
Three-Year Diploma Courses, after S.S.C. (10th standard) of the Board of Technical Education conducted by the Govt. of MH or its equivalent.
And
Non-zero score in Indira CET(UG)
Scholarships
At Indira University, we are committed to ensuring that education remains within reach for all. To support students who face financial challenges, we have established a range of scholarships. These awards are designed to remove economic barriers, allowing deserving learners to concentrate fully on their studies and build their future with confidence.

B.Sc. Artificial Intelligence and Data Science is an undergraduate program that focuses on AI concepts, machine learning, data analytics, and intelligent systems. It trains students to analyse data, build predictive models, and develop AI-driven solutions used across modern digital applications.
Yes, B.Sc. in AI and Data Science is worth pursuing in India due to growing adoption of AI across IT, finance, healthcare, manufacturing, and e-commerce. The increasing demand for data-driven decision-making has created strong career opportunities for AI and analytics professionals.
The scope of B.Sc. Artificial Intelligence and Data Science is strong, with opportunities in analytics, automation, machine learning, and AI development. Graduates can work across industries or pursue higher studies, certifications, and research as AI technologies continue to expand globally.
Career opportunities include roles such as Data Analyst, Machine Learning Engineer, AI Developer, Business Intelligence Associate, Data Engineer, and AI Research Assistant. These roles are available in IT services, analytics firms, startups, healthcare technology, fintech, and product companies.
The average starting salary after B.Sc. AI and Data Science typically ranges between ₹4–6 LPA. Salary levels depend on technical skills, project experience, job role, and industry, with higher packages possible for candidates with strong AI and data expertise.
Candidates must have completed 10+2 in the Science stream with Mathematics or an equivalent qualification. Diploma holders after SSC may also be eligible, subject to university and regulatory norms.
Pune and Pimpri–Chinchwad have multiple colleges offering B.Sc. AI and Data Science. While choosing a college, students should evaluate curriculum quality, faculty expertise, lab facilities, and industry exposure. Indira University’s School of Information Technology is recognized for its industry-aligned approach and infrastructure.











