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Online B.Sc in Generative AI
Planning to study Online B.Sc in Generative AI? Understand what to verify about the syllabus, prerequisites, delivery format and final qualification or certificate.
LevelUG ModeOnline Duration3 Years
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Course Overview
Online B.Sc in Generative AICourse Overview
Eligibility10+2 pass from a recognized board with a minimum of 45–50% marks.
Step into the future of technology with an Online B.Sc. in Generative AI, an undergraduate degree designed to prepare students for the rapidly evolving world of artificial intelligence.
Generative AI is transforming industries by enabling machines to generate human-like text, images, videos, audio, computer code and intelligent solutions. This program helps students understand how these technologies work and how to develop practical AI-powered applications.
Through a combination of theoretical knowledge, programming fundamentals, practical projects and industry-oriented learning, students can develop the technical expertise required to explore emerging opportunities in the AI industry.
What Makes This Program Exciting?
- Learn the fundamentals of Artificial Intelligence and Machine Learning.
- Explore Generative AI tools and technologies.
- Understand Large Language Models (LLMs) and neural networks.
- Develop skills in Python programming and data analytics.
- Explore prompt engineering and AI application development.
- Gain exposure to real-world AI projects and applications.
- Build a strong foundation for advanced studies and technology careers.
Your journey into the world of intelligent technology starts here!
Skills
Prepare yourself for the next generation of technology careers by developing highly relevant technical and professional skills.
Technical Skills
- Artificial Intelligence: Understand intelligent systems, AI concepts and real-world applications.
- Machine Learning: Learn how machines identify patterns and make predictions using data.
- Generative AI: Explore AI models capable of creating text, images, audio and other digital content.
- Python Programming: Develop programming skills for AI and machine learning applications.
- Prompt Engineering: Learn to create effective prompts to generate accurate and useful AI outputs.
- Deep Learning: Understand neural networks and advanced machine learning techniques.
- Natural Language Processing: Explore how computers understand and process human language.
- Data Analytics: Learn to interpret data and generate meaningful insights.
- Large Language Models: Understand the working principles and applications of LLMs.
- AI Application Development: Learn to build intelligent applications using modern AI technologies.
Professional Skills
- Analytical and logical thinking
- Problem-solving abilities
- Creativity and innovation
- Research and technical communication
- Team collaboration
- Project management
- Adaptability to emerging technologies
Who can apply?
Are you interested in technology, coding, innovation and intelligent machines? An Online B.Sc. in Generative AI can be an excellent academic choice for students who want to build a future in artificial intelligence.
Eligibility Criteria
- Students who have successfully completed Class 12 or an equivalent examination from a recognised board.
- Students from Science or Mathematics backgrounds may find the technical subjects particularly useful.
- Students interested in programming, computer science, data science and emerging technologies.
- Students who want to pursue undergraduate education through an online learning format.
- Working professionals seeking a foundation in artificial intelligence, subject to university eligibility requirements.
Who Should Choose This Course?
- Class 12 graduates interested in AI and technology.
- Students who want to explore future-oriented technology careers.
- Beginners interested in learning machine learning and programming.
- Aspiring AI developers and data science professionals.
- Students planning higher studies in Artificial Intelligence, Data Science or Computer Science.
Note: Mathematics, subject combinations, minimum marks and other eligibility conditions depend on the university offering the degree.
Skills
Prepare yourself for the next generation of technology careers by developing highly relevant technical and professional skills.
Technical Skills
- Artificial Intelligence: Understand intelligent systems, AI concepts and real-world applications.
- Machine Learning: Learn how machines identify patterns and make predictions using data.
- Generative AI: Explore AI models capable of creating text, images, audio and other digital content.
- Python Programming: Develop programming skills for AI and machine learning applications.
- Prompt Engineering: Learn to create effective prompts to generate accurate and useful AI outputs.
- Deep Learning: Understand neural networks and advanced machine learning techniques.
- Natural Language Processing: Explore how computers understand and process human language.
- Data Analytics: Learn to interpret data and generate meaningful insights.
- Large Language Models: Understand the working principles and applications of LLMs.
- AI Application Development: Learn to build intelligent applications using modern AI technologies.
Professional Skills
- Analytical and logical thinking
- Problem-solving abilities
- Creativity and innovation
- Research and technical communication
- Team collaboration
- Project management
- Adaptability to emerging technologies
Job Roles
Artificial Intelligence is creating new opportunities across technology, education, healthcare, finance, e-commerce, manufacturing and other industries. An Online B.Sc. in Generative AI can provide a foundation for exploring entry-level and specialised career pathways, depending on practical experience, technical proficiency and additional certifications.
| Job Role | Career Responsibilities |
|---|---|
| AI Developer | Develop and integrate AI-powered applications. |
| Junior Machine Learning Engineer | Assist in building and testing machine learning models. |
| Generative AI Associate | Work with generative AI tools and applications. |
| Prompt Engineer | Design and optimise prompts for AI systems. |
| Data Analyst | Analyse datasets and generate business insights. |
| Python Developer | Develop software applications using Python. |
| NLP Associate | Work on language-processing applications. |
| AI Research Assistant | Support AI research and experimentation. |
| Junior Data Scientist | Assist with data analysis and predictive modelling. |
| AI Automation Associate | Build and support AI-powered automation workflows. |
| AI Testing Associate | Evaluate AI application performance and outputs. |
| LLM Application Developer | Assist in developing applications using large language models. |
Potential Career Industries
- IT and Software Development
- Artificial Intelligence and Robotics
- Banking and Financial Services
- Healthcare and Medical Technology
- E-commerce and Digital Marketing
- Education Technology
- Business Automation
- Research and Development
Note: Career roles depend on individual skills, project experience, employer requirements and further qualifications. A degree does not guarantee employment.
Syllabus/Curriculum
The curriculum of an Online B.Sc. in Generative AI is designed to build knowledge progressively, starting with computer science fundamentals and advancing towards modern artificial intelligence technologies. Students can explore programming, mathematics, data science, machine learning, neural networks and generative AI through structured academic learning.
Indicative Semester-Wise Curriculum
| Semester | Subjects / Topics |
|---|---|
| Semester 1 | Introduction to Computer Science, Mathematics for Computing, Programming Fundamentals, Digital Literacy, Communication Skills |
| Semester 2 | Python Programming, Data Structures, Database Management Systems, Statistics and Probability, Computer Fundamentals |
| Semester 3 | Artificial Intelligence Fundamentals, Machine Learning, Data Analytics, Object-Oriented Programming, Linear Algebra |
| Semester 4 | Deep Learning, Neural Networks, Natural Language Processing, Data Visualisation, Cloud Computing Fundamentals |
| Semester 5 | Generative AI, Large Language Models, Prompt Engineering, Transformer Architecture, AI Ethics and Responsible AI |
| Semester 6 | AI Application Development, Retrieval-Augmented Generation (RAG), AI Automation, Model Evaluation, Industry Project and Internship |
Additional Learning Areas
- Computer Vision and Image Generation
- AI Chatbot Development
- Text-to-Image and Text-to-Audio Technologies
- AI-Powered Content Generation
- Generative AI APIs and Integration
- AI Security and Data Privacy
- Model Deployment and Performance Evaluation
Note: This is an indicative curriculum. The actual subjects, credits, semester structure and duration will be determined by the university's approved syllabus.
Why choose it ?
Artificial Intelligence is changing how businesses operate, how people communicate and how technology solves everyday problems. Choosing this degree can help students develop an academic foundation in one of the most exciting areas of modern computing.
- Future-Oriented Education: Explore emerging AI technologies and understand how intelligent systems are transforming different industries.
- Flexible Online Learning: Access learning resources and study through an online format without following a traditional daily classroom schedule.
- Industry-Relevant Technical Knowledge: Develop foundational knowledge of Python, machine learning, deep learning and generative AI applications.
- Learn Modern AI Technologies: Explore ChatGPT-style applications, LLMs, prompt engineering, AI automation and content-generation technologies.
- Practical Project Exposure: Apply theoretical concepts through programming exercises, case studies and AI-based academic projects.
- Multiple Career Pathways: Prepare for opportunities in software development, AI applications, data analytics and related technology fields.
- Affordable Learning Opportunities: Explore university fee structures and payment options that may make undergraduate education more accessible.
- Higher Education Opportunities: Build a foundation for further studies in computer science, artificial intelligence, machine learning and data science, subject to the admission requirements of the chosen institution.
- Develop Creative Problem-Solving Skills: Learn how to use intelligent technology to approach real-world challenges.
- Stay Ahead in the Digital Era: Gain exposure to technologies that are increasingly becoming part of modern business and technological innovation.
Learning Module
The learning modules are designed to provide a structured and engaging educational experience, helping students move from beginner-level concepts to advanced AI applications.
| Learning Module | What You Will Learn |
|---|---|
| Module 1: Computer Science Foundation | Understand computer systems, programming logic and computational thinking. |
| Module 2: Programming with Python | Learn coding, functions, libraries and programming applications. |
| Module 3: Mathematics for AI | Explore statistics, probability, calculus and linear algebra. |
| Module 4: Introduction to AI | Understand intelligent systems, AI models and automation. |
| Module 5: Machine Learning | Learn supervised, unsupervised and reinforcement learning fundamentals. |
| Module 6: Deep Learning | Explore neural networks, model training and advanced learning techniques. |
| Module 7: Generative AI Technologies | Understand generative models and AI-generated content. |
| Module 8: Prompt Engineering | Develop effective prompts and improve AI-generated results. |
| Module 9: Large Language Models | Explore LLM architecture, applications and model limitations. |
| Module 10: AI Project Development | Create practical AI-based projects and demonstrate technical knowledge. |
Practical Learning Activities
- Python coding exercises
- AI chatbot development
- Prompt creation challenges
- Machine learning experiments
- Data analysis assignments
- Generative AI application demonstrations
- Final-year capstone projects
Examination Pattern
The Online B.Sc. in Generative AI follows the examination and evaluation structure prescribed by the respective university. The assessment process may combine continuous evaluation with end-semester examinations to measure students' conceptual understanding, technical knowledge and practical learning.
Possible Assessment Components
| Assessment Type | Description |
|---|---|
| Internal Assessment | Evaluates regular academic performance. |
| Online Assignments | Tests understanding of concepts through assignments. |
| Quizzes and MCQs | Measures subject knowledge and learning progress. |
| Practical Projects | Evaluates programming and application-development skills. |
| Case Studies | Tests analytical and problem-solving abilities. |
| Semester Examinations | Assesses overall understanding of each subject. |
| Project Evaluation | Measures the ability to apply concepts to practical problems. |
Examination Features
- Online examination facilities, as permitted by university regulations.
- Proctored examination arrangements where applicable.
- Continuous academic assessment.
- Digital assignment submission.
- Semester-wise performance evaluation.
- Results and academic updates through the university portal.
Note: The examination mode, passing criteria, marks distribution and practical assessment requirements depend on the university's approved academic regulations.
Approvals
Before enrolling in an Online B.Sc. in Generative AI, students should verify the university's recognition and the programme's eligibility for delivery in online mode.
Important Regulatory Considerations
- UGC Recognition: The degree-awarding university should be recognised by the University Grants Commission (UGC).
- UGC-DEB Entitlement / Recognition: The university must be eligible and the specific programme must be permitted for online delivery for the relevant academic session.
- Degree Validity: Degrees awarded in conformity with applicable UGC regulations by recognised or entitled institutions are treated as equivalent to corresponding conventional-mode degrees.
- NAAC Accreditation: Check the university's NAAC accreditation status, where applicable.
- AICTE Approval: Check whether any additional approval is applicable to the particular institution and programme.
- Academic Transparency: Review the official syllabus, fee details, faculty information and admission guidelines before enrolling.
Important: UGC recognition of a university does not automatically mean that every programme offered by that university is approved for online delivery. Verify the exact programme and academic session on the official UGC Distance Education Bureau (UGC-DEB) portal.
Fee Structure
Make your career aspirations achievable with a flexible and accessible online learning option. The Online B.Sc. in Generative AI fee structure is determined by the university, programme duration and available academic facilities.
Fee Components
| Fee Type | Details |
|---|---|
| Registration Fee | One-time admission registration charges, if applicable. |
| Tuition Fee | Academic fee for the programme. |
| Examination Fee | Charges for semester examinations, if applicable. |
| Technology Fee | Online learning platform charges, if applicable. |
| Study Material Fee | Digital or additional academic resources, if applicable. |
| Total Programme Fee | Overall fee payable for the complete degree. |
Flexible Payment Options
- Semester-wise fee payment.
- Annual fee payment options.
- Instalment facilities, where available.
- Online fee payment facilities.
- University-approved scholarships or concessions, where applicable.
Get Your Fee Details Today!
Looking for an affordable way to enter the world of Artificial Intelligence? Connect with our admission counsellors to explore the latest university fee structure, payment options and available admission benefits. Find the right learning opportunity for your future.
Placement Assistance
Turn your academic knowledge into professional opportunities with career guidance and placement support. An Online B.Sc. in Generative AI can help students develop the foundational technical knowledge needed to explore opportunities in the growing AI and technology ecosystem.
Placement Assistance Features
Career Counselling
Receive guidance to identify suitable career pathways based on your interests, academic background and technical skills.
Resume Building Support
Learn how to create a professional, ATS-friendly resume highlighting programming knowledge, academic achievements and AI projects.
Interview Preparation
Prepare for technical and HR interviews through practice questions, mock interviews and interview guidance.
Technical Skill Development
Strengthen your understanding of Python, machine learning, data analytics and generative AI applications.
Project Portfolio Development
Showcase your technical abilities through academic projects, AI applications and practical assignments.
Internship Guidance
Explore relevant internship opportunities to gain exposure to professional working environments.
Career Opportunities
Get guidance on exploring job openings across AI, software development, data analytics and technology-related industries.
Industry Interaction
Participate in available webinars, expert sessions and career-oriented learning activities.
Potential Employment Sectors
- Artificial Intelligence Companies
- IT and Software Development Companies
- Data Analytics Organisations
- FinTech Companies
- Healthcare Technology
- EdTech Companies
- Digital Marketing Agencies
- Technology Startups
Build Skills Today. Prepare for Tomorrow's Opportunities!
Please note: Placement assistance, internships, interview preparation and recruitment opportunities depend on the facilities offered by the university. Employment and salary outcomes are not guaranteed.
Admission Process
Starting your journey towards an exciting career in Artificial Intelligence is simple. Follow these steps to apply for the Online B.Sc. in Generative AI.
- Explore the Programme Understand the course structure, eligibility requirements, duration and available learning facilities.
- Submit the Enquiry Form Share your basic contact details to receive programme information and admission guidance.
- Check Eligibility Verify your Class 12 qualification and other admission requirements.
- Complete the Application Form Fill in the university's official online application form with accurate personal and academic details.
- Upload Required Documents Submit the necessary educational and identity documents for verification.
- Pay the Admission Fee Complete the payment through the university's authorised payment portal.
- Admission Confirmation Receive admission confirmation after successful verification and fulfilment of the university's requirements.
- Start Learning Access the online learning platform and begin your academic journey.
Take the First Step Towards Your AI Career! Apply today and explore the possibilities of studying Generative AI through an online undergraduate programme.
Required Documents
Students applying for an Online B.Sc. in Generative AI may need to submit the following documents during the admission process.
Academic Documents
- Class 10th marksheet and certificate.
- Class 12th marksheet and certificate.
- Transfer Certificate (TC), if required.
- Migration Certificate, if required.
- Other academic certificates, if applicable.
Identity and Personal Documents
- Aadhaar Card or another accepted identity proof.
- Recent passport-size photograph.
- Scanned signature.
- Valid email address.
- Active mobile number.
- Address proof, if required.
Additional Documents
- Category certificate, if applicable.
- Disability certificate, if applicable.
- ABC ID / APAAR ID, where required.
- DEB ID, where applicable under UGC requirements.
- Any additional documents requested by the university.
Note: Document requirements may vary depending on the university's admission guidelines.
STUDENT GUIDELINES
UGC Refund Policy
The University Grants Commission (UGC) has established guidelines regarding fee refunds when students cancel or withdraw their admission from higher education institutions. Students enrolling in the Online B.Sc. in Generative AI should review the applicable UGC fee refund guidelines and the university's official refund policy before making payment. Where the October 2018 UGC refund framework applies, the following percentage-based structure is prescribed:
1. UGC's General Refund Framework
| 15 days or more before the last admission date | 100% |
|---|---|
| Less than 15 days before the last admission date | 90% |
| Up to 15 days after the last admission date | 80% |
| More than 15 days but within 30 days after the last admission date | 50% |
| More than 30 days after the last admission date | 0% |
The applicable processing deduction for a 100% refund is governed by the relevant UGC notification. The framework and any subsequent UGC directions must be checked for the admission session concerned.
Official document: View UGC Refund Policy (PDF)
Official document: View UGC Refund Policy (PDF)
2. Important Refund Considerations
Students should submit a formal admission cancellation or withdrawal request to the university. Refund eligibility depends on the date of withdrawal and the officially notified last date of admission. Applicable processing charges and deductions must follow the relevant UGC guidelines, and eligible refunds should be processed according to the applicable regulatory timelines. Students should retain their fee receipts and cancellation acknowledgement for future reference.
Important: Confirm the latest applicable refund rules using official sources. Visit the UGC Official Website for official notices and information.
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Let’s clear up some doubts
Are there exams or assessments in Online B.Sc in Generative AI?
Value is more than the headline fee. Compare the depth of the curriculum, trainer access, practical projects, support, assessment and the credibility of the resulting qualification or certificate, where applicable.
What should I know before choosing Online B.Sc in Generative AI?
Build a shortlist by checking the course content, prerequisites, format, time commitment, full cost and outcomes against your own priorities. Verify any claims about rankings, recognition or placement support from reliable current sources.
How can I compare providers offering Online B.Sc in Generative AI?
The topics can differ between providers. Read the current syllabus for Online B.Sc in Generative AI and look for the core modules, practical work, assessments and any elective choices. Treat a general course description as a starting point, not a substitute for the full curriculum.
Can beginners apply for Online B.Sc in Generative AI?
It may be possible, but the timetable matters. Before enrolling in Online B.Sc in Generative AI, check live-session timings, attendance rules, assignment deadlines and exam dates against your work and personal commitments.
Who is Online B.Sc in Generative AI most suitable for?
Ask for an itemised cost breakdown for Online B.Sc in Generative AI, including tuition, registration, examination, software, materials and any other compulsory charges. Confirm instalment dates, cancellation rules and refund terms before paying.
What costs should I check before enrolling in Online B.Sc in Generative AI?
Recognition depends on the provider, qualification and intended use. Check relevant official regulator or accreditor records and, if needed, confirm acceptance with the employer, licensing body or institution where you plan to use the qualification.
What documents might I need for Online B.Sc in Generative AI?
Some courses welcome beginners, while others assume prior study or professional experience. Check the prerequisite list for Online B.Sc in Generative AI and ask the provider whether preparatory learning is recommended if you are new to the subject.
What does the learning plan for Online B.Sc in Generative AI usually cover?
Ask how to contact faculty or trainers, access learning materials, get technical help and resolve academic questions. For online learning, also confirm whether sessions are recorded and how long you can access course resources.
What should I ask the admissions team about Online B.Sc in Generative AI?
Start with the exact outcome you want from Online B.Sc in Generative AI, then check the current course outline, entry rules, schedule and total cost. The title alone may not tell you what is included, so ask the provider to clarify anything important before you commit.
How should I evaluate the value of Online B.Sc in Generative AI?
There is no single duration that applies to every provider. Check the published study period, term or semester structure, pace options and any maximum completion window for Online B.Sc in Generative AI before planning your schedule.