B.Sc – Artificial Intelligence and Machine Learning
Think Beyond Limits – Start Your Journey to Becoming an AI Innovator
The B.Sc. in Artificial Intelligence and Machine Learning is a transformative program designed to provide students with a comprehensive understanding of the principles, methodologies, and applications of AI and ML technologies.
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Course Duration:
3 Years
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Course Fees:
₹2,53,600*
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Mode of Learning:
Online
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Medium of Instruction:
English
Tailored for aspiring tech professionals, the program equips learners with the skills to develop intelligent systems capable of solving complex, real-world challenges across diverse domains. Graduates will gain expertise in AI and ML concepts, algorithms, and programming frameworks while fostering analytical and problem-solving abilities. This program also emphasizes ethical and societal considerations, preparing students to responsibly innovate and make a meaningful impact in the fast-evolving world of AI and ML.
Key Benefits of Bachelor of Science in Artificial Intelligence and Machine Learning
Master the Core Concepts of AI and ML
Gain a deep understanding of artificial intelligence and machine learning principles, including algorithms, data structures, and computational theory. These foundational concepts will enable you to tackle real-world challenges with innovative AI-driven solutions.
Practical Expertise with Cutting-Edge Tools
Become proficient in programming languages and AI/ML frameworks that are critical in developing intelligent systems. You'll gain hands-on experience in tools that will empower you to build and implement AI/ML solutions across various applications.
Develop Critical Problem-Solving Skills
Equip yourself with the skills to analyze complex problems and develop effective AI and ML solutions by applying advanced mathematical, computational, and analytical methods. You'll be prepared to solve pressing challenges in diverse industries.
Understand Ethical, Legal, and Societal Implications
Develop a deep understanding of the ethical, legal, and societal implications of AI and ML technologies. You will be equipped to ensure your professional practice adheres to ethical standards and promotes positive social impact.
Expert Faculty and Industry Insights
Learn from expert faculty members and industry professionals who bring both academic knowledge and practical insights into the classroom. This exposure will help you understand how AI and ML are transforming industries globally.
Program Highlights
- Earn a Prestigious B.Sc. Degree from IIIT Vadodara
- Learn from Renowned IIIT Vadodara Faculty
- Industry-Relevant Skills for Future Careers
- Innovative Research Opportunities
- Flexible online learning environment
Program Objectives
- Gain comprehensive knowledge of the theoretical principles and practical methodologies behind Artificial Intelligence and Machine Learning.
- Learn to create intelligent systems and solutions capable of solving complex problems across various domains, from business to healthcare.
- Learn how to integrate AI and ML with other fields such as computer science, engineering, business, and healthcare to develop well-rounded solutions.
- Develop advanced problem-solving and analytical skills, enabling you to apply AI and ML techniques to real-world challenges with confidence.
- Master programming languages and AI/ML tools and frameworks, ensuring you’re equipped to design, implement, and evaluate advanced AI and ML solutions.
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.
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 Computer Science |
| CS161 | Computer System Tools |
| CS103 | Computer Programming and Problem Solving (C) |
| CS163 | Computer Programming and Problem Solving Lab |
Semester II
| Course Code | Course Name | |
|---|---|---|
| BSCAIML 201 | Object Oriented Programming | |
| BSCAIML 202 | Object Oriented Programming Lab | |
| BSCAIML 203 | Probability and Statistics | |
| BSCAIML 204 | Computer Organization and Architecture | |
| BSCAIML 205 | Elective | |
| BSCAIML 206 | Elective Lab | |
| BSCAIML 206 | Communication Skill - 2 | |
| 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 |
|---|---|
| BSCAIML 301 | Data Structures and Algorithms |
| BSCAIML 302 | Data Structures and Algorithms Lab |
| BSCAIML 303 | Python Programming |
| BSCAIML 304 | Python Programming Lab |
| BSCAIML 305 | DBMS |
| BSCAIML 306 | DBMS Lab |
| BSCAIML 307 | Introduction to Software Engineering |
| BSCAIML 308 | Human Values and Ethics |
| BSCAIML 309 | Seminar |
Semester IV
| Course Code | Course Name | |
|---|---|---|
| BSCAIML 401 | Computer Networks | |
| BSCAIML 402 | Computer Networks Lab | |
| BSCAIML 403 | Introduction to Operating System | |
| BSCAIML 404 | Exploratory Data Analysis and Visualization | |
| BSCAIML 405 | Exploratory Data Analysis and Visualization Lab | |
| BSCAIML 406 | Fundamental of Machine Learning | |
| BSCAIML 407 | Internship / Project | |
| 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 V
| Course Code | Course Title | |
|---|---|---|
| BSCAIML 501 | Machine Learning Techniques | |
| BSCAIML 502 | Machine Learning Techniques Lab | |
| BSCAIML 503 | Basics of Natural Language Processing | |
| BSCAIML 504 | Research Methodology | |
| BSCAIML 505 | Elective | |
| BSCAIML 506 | Elective Lab | |
| BSCAIML 507 | Mini 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 | |
Semester VI
| BSCAIML 601 | Deep Learning Techniques |
| BSCAIML 602 | Deep Learning Techniques Lab |
| BSCAIML 603 | Elective – 1 |
| BSCAIML 604 | Elective – 2 |
| BSCAIML 605 | Major Project |
Program Outcomes:
- Graduates will possess a strong foundation in the core concepts and techniques of artificial intelligence and machine learning, including algorithms, data structures, statistical methods, and computational theory.
- Graduates will be proficient in programming languages, software development, and the use of AI and ML tools and frameworks, enabling them to design, implement, and evaluate AI and ML solutions for various applications.
- Graduates will demonstrate the ability to analyze complex problems, identify appropriate AI and ML techniques, and develop effective solutions by applying mathematical, computational, and analytical methods.
- Graduates will be equipped to engage in research and development activities, contributing to advancements in AI and ML through innovative approaches and original research, while staying current with emerging trends and technologies.
- Graduates will be capable of integrating AI and ML knowledge with other domains such as computer science, engineering, business, and healthcare, enabling them to develop comprehensive and multidisciplinary solutions.
- Graduates will understand the ethical, legal, and societal implications of AI and ML technologies, and will be prepared to address these considerations responsibly, ensuring that their professional practice adheres to ethical standards and promotes positive social impact.
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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FAQs
- What is the aim of the B.Sc. in Artificial Intelligence and Machine Learning program?
The program provides an in-depth understanding of AI and ML, focusing on theoretical foundations and applications to develop intelligent systems - What are the eligibility criteria for this program?
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 - What key concepts will students learn?
Students will master algorithms, data structures, statistical methods, computational theory, and frameworks covered under a B.Sc. in Artificial Intelligence and Machine Learning. - What practical skills will students gain?
Graduates will be proficient in programming languages, software development, and designing solutions as part of their B.Sc. Artificial Intelligence and Machine Learning training. - How is the curriculum designed for industry relevance?
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.
Admission Process
Online Application
Payment of Application Fees
(Non Refundable)
Document Verification
Payment of Admission Fees
