B.Sc - Artificial Intelligence & Machine Learning - Online
Build the Skills for Tomorrow's AI-Driven World
Earn a B.Sc. Degree from IIIT Vadodara
Learn from IIIT Vadodara Faculty
Flexible Online Learning Environment
Last Date to Apply: 13th January, 2026 | 2nd Cohort of B.Sc. AI & ML Begins: 13th January 2026
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Course Duration:
3 Years
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1st Semester Fees:
₹55,100
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Mode of Learning:
Online
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Medium of Instruction:
English
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Schedule :
Mon-Friday : 6:30PM-9:30PM
Saturday : 9:00AM-3:30PM
Sunday : 9:00AM-10:00AM
Artificial Intelligence and Machine Learning are transforming the way businesses operate, decisions are made and innovations are built. The B.Sc. in Artificial Intelligence & Machine Learning from IIIT Vadodara provides learners with a strong foundation in programming, machine learning, data science and intelligent systems through a curriculum designed for the future of technology.
Designed for flexibility, the Program enables learners to pursue a degree from IIIT Vadodara while balancing their academic, personal or professional commitments.
Program Objectives
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01
Gain comprehensive knowledge of the theoretical principles and practical methodologies behind Artificial Intelligence and Machine Learning.
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02
Learn to create intelligent systems and solutions capable of solving complex problems across various domains, from business to healthcare.
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03
Learn how to integrate AI and ML with other fields such as computer science, engineering, business, and healthcare to develop well-rounded solutions.
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04
Develop advanced problem-solving and analytical skills, enabling you to apply AI and ML techniques to real-world challenges with confidence.
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05
Master programming languages and AI/ML tools and frameworks, ensuring you're equipped to design, implement, and evaluate advanced AI and ML solutions.
Benefits of the Program
Graduate from IIIT Vadodara
Earn a B.Sc. degree from an Institute of National Importance, recognised for academic excellence and innovation.
Learn from IIIT Vadodara Faculty
Build a strong academic foundation through faculty-led instruction and a future-focused AI & ML curriculum.
Flexible Learning Experience
Attend live online sessions and access recorded learning resources, allowing you to learn at your own pace while balancing other commitments.
Industry-Relevant Curriculum
Study emerging technologies including Machine Learning, Deep Learning, Computer Vision, Natural Language Processing and Generative AI.
Future-Ready Skills
Develop the technical knowledge and analytical skills required to pursue opportunities in the rapidly evolving AI ecosystem.
Program Certificate
Course Eligibility:
For Indian Applicants
- Class 12 or equivalent (list of equivalents)
- The final examination of the 10+2 system, conducted by a Central or State Board recognized by the Association of Indian Universities (AIU).
- Intermediate or two-year Pre-University examination conducted by a Board or University recognized by the Association of Indian Universities.
- Final examination of the two-year course of the Joint Services Wing of the National Defence Academy.
- Senior Secondary School Examination conducted by the National Institute of Open Schooling with a minimum of five subjects.
- Any Public School, Board or University examination in India or in a foreign country recognised as equivalent to the 10+2 system by the AIU.
- H.S.C. vocational examination.
- A Diploma recognized by the All India Council for Technical Education (AICTE) or a State Board of Technical Education of at least 3 years duration.
- General Certificate Education (GCE) examination (London, Cambridge or Sri Lanka) at the Advanced (A) level.
- High School Certificate Examination of the Cambridge University or International Baccalaureate Diploma of the International Baccalaureate Office, Geneva.
- Candidates who have completed Class XII (or equivalent) examination outside India or from a Board not specified above should produce a certificate from the AIU to the effect that the examination they have passed is equivalent to the Class XII examination.
- In case the Class XII examination is not a public examination, the candidate must have passed at least one public (Board or Pre-University) examination earlier.
For International Applicants
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For International Applicants Only: If an applicant has obtained their senior secondary/high school education from an institution located outside of India: they must provide an Equivalence Certificate issued by the Association of Indian Universities - which recognises their senior secondary/high school education as equivalent to Class 12 certificate issued from a recognised central or state board in India.
- The process to apply for an equivalence Certificate is detailed here
(https://www.aiu.ac.in/evaluation.php) - To apply for Equivalence, students must start by applying here
(https://evaluation.aiu.ac.in/Student/login/) - If an applicant’s educational documents (mark sheets and certificates) were issued in a language other than English: they must provide copies of such documents translated into English by a sworn translator.
Program Highlights
- 3-Year Undergraduate Program
- Graduate from IIIT Vadodara
- Innovative Research Opportunities
- Flexible Online Learning
- Live Faculty Sessions
- Learn from IIIT Vadodara Faculty
Course Structure
Semester I
| Course Code | Course Name |
|---|---|
| MA101 | Mathematics - I (Discrete Mathematics) |
| SC101 | Environment Sustainability and Climate Change |
| IK101 | Introduction to Yoga |
| HS101 | Spoken and Written Communication |
| CS101 | Introduction to Artificial Intelligence |
| CS161 | Computer System Tools |
| CS103 | Computer Programming and Problem Solving (C) |
| CS163 | Computer Programming and Problem Solving Lab |
Semester II
| Course Code | Course Name | |
|---|---|---|
| MA102 | Mathematics-II (Linear Algebra) | |
| IK102 | Introduction to Vedic Mathematics | |
| CS112 | Data Visualization and Analytics (Python) | |
| CS104 | Operating Systems | |
| CS106 | Introduction to Data Structures | |
| CS166 | Introduction to Data Structures Lab | |
| CS108 | Object Oriented Programming (Java) | |
| CS168 | Object Oriented Programming Lab | |
| Elective | ||
| BSCAIML 207 | Web Analytics | |
| BSCAIML 208 | Web Analytics Lab | |
| BSCAIML 209 | Advance MS-Office | |
| BSCAIML 210 | Advance MS-Office Lab | |
Semester III
| Course Code | Course Name |
|---|---|
| MA201 | Mathematics - III (Probability and Statistics) |
| MG201 | Introduction to Entrepreneurship |
| CS201 | Design and Analysis of Algorithms |
| CS261 | Design and Analysis of Algorithms Lab |
| CS203 | Database Management Systems |
| CS263 | Database Management Systems Lab |
| CS205 | Computer Organization and Architecture |
| CS265 | Computer Organization and Architecture Laboratory |
Semester IV
| Course Code | Course Name |
|---|---|
| MA204 | Mathematics - IV (Optimization Methods) |
| CS202 | Machine Learning |
| CS262 | Machine Learning Lab |
| CS204 | Software Engineering |
| CS264 | Software Engineering Lab |
| CS206 | Artificial Intelligence |
| CS266 | Artificial Intelligence Lab |
| CS268 | Statistics in R |
| CS208 | Web Technology and DevOps |
Semester V
| Course Code | Course Name | |
|---|---|---|
| CS301 | Deep Learning | |
| CS303 | Introduction to Robotics | |
| CS305 | Natural Language Processing | |
| CS311 | AI-ML Ops | |
| CS309 | Image and Video Processing | |
| HS301 | Artificial Intelligence and Ethics | |
| PI301 | Summer Internship/ Training | |
| Elective | ||
| BSCAIML 508 | Artificial Neural Networks | |
| BSCAIML 509 | Artificial Neural Networks Lab | |
| BSCAIML 510 | Big Data | |
| BSCAIML 511 | Big Data Lab Lab | |
| BSCAIML 512 | Data Mining | |
| BSCAIML 513 | Data Mining lab | |
| BSCAIML 514 | IoT | |
| BSCAIML 515 | IoT Lab | |
Semester VI
| Course Code | Course Name | |
|---|---|---|
| CS302 | Reinforcement Learning | |
| PI302 | B.Sc. Project | |
| Elective | ||
| BSCAIML 606 | Computer Vision | |
| BSCAIML 607 | Cyber Security | |
| BSCAIML 608 | Cloud Computing | |
| BSCAIML 609 | AI in Healthcare | |
| BSCAIML 610 | Introduction to R | |
| BSCAIML 611 | Information Security and Cyber Laws | |
| BSCAIML 612 | Predictive Analytics | |
Fee Structure
| Fees Components | Sem I | Sem II | Sem III | Sem IV | Sem V | Sem VI | ||
| Caution Deposit (Refundable) | 10000 | 10000 | - | - | - | - | ||
| I Card Fee (One time) | 100 | - | - | - | - | - | ||
| Institute Development Contribution (IDC) (One time) | - | - | - | - | - | - | ||
| Tuition Fee | 37500 | 37500 | 37500 | 37500 | 37500 | 37500 | ||
| Campus Immersion Fee (optional) | 3000 | - | - | - | - | 3000 | ||
| Institute Registration Fees | 1000 | 1000 | 1000 | 1000 | 1000 | 1000 | ||
| Alumni Fee | 1000 | 1000 | 1000 | 1000 | 1000 | 1000 | ||
| Convocation Fee | 1000 | 1000 | 1000 | 1000 | 1000 | 1000 | ||
| Life Insurance* | 100 | 100 | 100 | |||||
| Medical Insurance* | 1400 | 1400 | 1400 | |||||
| Total | 55100 | 50500 | 42000 | 40500 | 42000 | 43500 | ||
Note:
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Program Outcomes:
- Build a strong foundation in Artificial Intelligence, Machine Learning, programming and computational thinking.
- Develop AI and Machine Learning solutions using modern tools and technologies.
- Apply analytical thinking to solve practical problems using intelligent systems.
- Explore emerging AI technologies and their applications across industries.
- Develop research, innovation and problem-solving capabilities.
- Understand ethical and responsible AI practices.
Admission Process
Online Application
Payment of Application Fees
(Non Refundable)
Document Verification
Payment of Admission Fees
Acknowledgement
FAQs
The program provides an in-depth understanding of AI and ML, focusing on theoretical foundations and
applications to develop intelligent systems.
Applicants need 10+2 in Science with a minimum of 60% and a valid score in recognized national or
international entrance exams. Relaxations are available for specific categories.
Students will master algorithms, data structures, statistical methods, computational theory, and
frameworks covered under a B.Sc. in Artificial Intelligence and Machine Learning.
Graduates will be proficient in programming languages, software development, and designing solutions
as part of their B.Sc. Artificial Intelligence and Machine Learning training.
The curriculum integrates cross-functional business knowledge with computer technologies to solve
real-world problems, making the B.Sc. in AI and ML program highly industry-oriented.
Batch Orientation - 2025
