B.Tech in Artificial Intelligence and Data Science with Curriculum Aligned to NVIDIA Deep Learning Institute (DLI)
Duration4 Years
Course Fee12.90 Lakhs
Eligibility10+2 *
Artificial Intelligence (AI) and Data Science are revolutionizing every sector of the global economy by enabling intelligent automation, predictive decision-making, and data-driven innovation.
From healthcare, finance, manufacturing, and agriculture to smart cities, cybersecurity, and autonomous systems, AI technologies are transforming the way organizations solve complex challenges and create sustainable value. As industries rapidly embrace digital transformation, the demand for highly skilled AI and Data Science professionals continues to grow across the world.
Program Specialisation
The B.Tech in AI & DS at GD Goenka University is a future-oriented undergraduate programme designed to develop the next generation of AI innovators, data scientists, and technology leaders.
Aligned with the University’s vision of fostering academic excellence, innovation, research, and industry readiness, the programme combines a strong foundation in Computer Science with cutting-edge technologies including Machine Learning, Deep Learning, Generative AI, Natural Language Processing, Computer Vision, Big Data Analytics, Cloud Computing, Internet of Things (IoT), and Intelligent Decision Systems.
Along with fundamentals subjects in programming, Statistics and Mathematics, Data Analytics, Applications of Artificial Intelligence, coding competition initiatives and Industry Internships.
The curriculum follows an interdisciplinary and experiential learning approach, integrating theoretical foundations with extensive laboratory work, industry projects, internships, hackathons, innovation challenges, and research-driven learning. Students gain hands-on experience in designing intelligent algorithms, developing predictive models, analysing large-scale datasets, and deploying AI-powered applications capable of addressing real-world problems.
GD Goenka University provides a vibrant ecosystem that promotes innovation and entrepreneurship through its advanced research facilities, Centres of Excellence, and incubation ecosystem. Students benefit from exposure to state-of-the-art infrastructure, including the University’s Dell–NVIDIA AI Lab, advanced computing facilities, and the Centre of Excellence in Industry 4.0, enabling them to work on high-performance AI, deep learning, industrial automation, robotics, IoT, and smart manufacturing applications.
The programme is further strengthened through collaborations with leading technology organizations and academic partners, including IBM, Red Hat Academy, Microsoft Cloud Technologies, and other industry collaborators. These partnerships enrich the curriculum through certification opportunities, industry mentoring, live projects, internships, and exposure to emerging technologies, ensuring that students graduate with industry-relevant competencies.
Program Highlights:
BTech Artificial Intelligence and Data Science programme is an advanced programme designed to place you on a high-growth career trajectory, That offers industry exposure, modern infrastructure, expert faculty, internships, skill development, and holistic campus learning Experiences.
MAJOR HIGHLIGHTS:
- Industry aligned programmes.
- Exceptional infrastructure including the state-of-the-art iMac Lab.
- Collaborations with leading technology partners like IBM and RedHat Academy.
- An invigorating environment for pursuing research.
- Extensive industry exposure through webinars, conferences and internships.
Program Specific Outcomes (PSO)
PSO 01
Apply algorithmic thinking and vibe coding skills to develop and maintain efficient and robust computing systems.
PSO 02
Solve real-world problems using technology while adapting to AI-driven innovations through collaboration, ethics, and continuous learning.
PSO 03
Apply mathematical, statistical, and data analytics techniques to analyze large-scale data and extract meaningful insights for data-driven business and scientific decision-making.
Programme Outcomes (PO)
Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
Identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.
Design solutions for complex engineering problems and design system components or processes that meet the specified needs with appropriate consideration for the public health and safety, and the cultural, societal, and environmental considerations.
Use research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions.
Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modeling to complex engineering activities with an understanding of the limitations.
Apply reasoning informed by the contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the professional engineering practice.
Understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development.
Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
Communicate effectively on complex engineering activities with the engineering community and with society at large, such as, being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions.
Demonstrate knowledge and understanding of the engineering and management principles and apply these to one’s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments.
Recognize the need for, and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change.
Curriculum Details
| Course Code | Course Title | L | T | P | Credits |
|---|---|---|---|---|---|
| MAT1119 | Matrix Methods and Linear Algebra | 3 | 1 | 0 | 4 |
| COM1531 | Contemporary English | 0 | 0 | 4 | 2 |
| PHY1009/ | Elements of Modern Physics/ Elements of Modern Physics Lab | 3 | 0 | 2 | 4 |
| CSE1010/ CSE1010L | Problem Solving through Programming / Programming and Problem Solving Lab | 3 | 0 | 2 | 4 |
| CSE1711 | Artificial Intelligence and its Real-World Applications | 2 | 0 | 0 | 2 |
| VAC001 | Design Thinking | 2 | 0 | 0 | 2 |
| EGR1501 | Induction Program | 0 | 0 | 0 | 0 |
| Total Credits | 18 | ||||
| Course Code | Course Title | L | T | P | Credits |
|---|---|---|---|---|---|
| MAT1120/MAT1120L | Probability and Statistics using Python/Probability and Statistics using Python Lab | 3 | 0 | 2 | 4 |
| PHY1008/PHY1008L | Quantum Mechanics/Quantum Mechanics Lab | 3 | 0 | 2 | 4 |
| ELE1001/ELE1001L | Fundamentals of Electrical and Electronics Engineering/ Fundamentals of Electrical and Electronics Engineering Lab | 3 | 0 | 2 | 4 |
| CSE1009/CSE1009L | Data Structures /Data Structures Lab | 3 | 0 | 2 | 4 |
| COM1542 | Professional Skills and Ability Enhancement | 0 | 0 | 4 | 2 |
| LAW1010 | Introduction to the Indian Constitution | 3 | 0 | 0 | 0 |
| VAC004 | Introduction to Indian Knowledge System | 2 | 0 | 0 | 2 |
| MEC1509 | Engineering Graphics | 0 | 0 | 4 | 2 |
| Total Credits | 22 | ||||
| Course Code | Course Title | L | T | P | Credits |
|---|---|---|---|---|---|
| MAT1123 / MAT1123L | Discrete Mathematical Structures / Discrete Mathematical Structures Lab | 3 | 0 | 2 | 4 |
| CSE2036/CSE2036L | Programming using Java/Programming using Java Lab | 3 | 0 | 2 | 4 |
| ELX2705 | Digital Logic Design | 2 | 0 | 0 | 2 |
| CSE2034/CSE2034L | Introduction to Design and Analysis of Algorithms/ Introduction to Design and Analysis of Algorithms Lab | 3 | 0 | 2 | 4 |
| UHV2701 | Universal Human Values | 3 | 0 | 0 | 3 |
| IDP2501/IDP2502 | Developing a Business Model/Research & Design | 0 | 1 | 4 | 3 |
| Total Credits | 20 | ||||
| Course Code | Course Title | L | T | P | Credits |
|---|---|---|---|---|---|
| CSE2047/ | Operating Systems: The System that makes computer works Operating Systems: The System that makes computer works Lab | 3 | 0 | 2 | 4 |
| CSE2711 | Computer Organization and Architecture | 3 | 1 | 0 | 4 |
| CSE2037/CSE2037L | Basics of Data Communication and Computer Networks/ Basics of Data Communication and Computer Networks Lab | 3 | 0 | 2 | 4 |
| CSE2717 | Introduction to Data Science | 3 | 0 | 0 | 3 |
| CSE2732 | AI Ethics and Responsible Computing | 2 | 0 | 0 | 2 |
| IDP2503/IDP2504 | Translating Business Model/ Data Analysis & Publication | 0 | 1 | 4 | 3 |
| ENV1705 | Environmental Studies | 2 | 0 | 0 | 0 |
| Total Credits | 20 | ||||
| Course Code | Course Title | L | T | P | Credits |
|---|---|---|---|---|---|
| CSE 3053 / CSE3053L | Data Visualization using R / Data Visualization using R Lab | 3 | 0 | 2 | 4 |
| CSE3727 | Advanced Artificial Intelligence | 2 | 1 | 0 | 3 |
| ELX3008/ELX3008L | Microprocessor and Microcontrollers/ Microprocessor and Microcontrollers Lab | 3 | 0 | 2 | 4 |
| Professional Elective-I | 3 | 1 | 0 | 4 | |
| CSE3022/ | DBMS with NoSQL/DBMS with NoSQL Lab | 3 | 0 | 2 | 4 |
| CSE3723 | Cloud Computing | 3 | 0 | 0 | 3 |
| Total Credits | 22 | ||||
| Course Code | Course Title | L | T | P | Credits |
|---|---|---|---|---|---|
| CSE 3046 / CSE3046L | Data Warehousing and Data Mining / Data Warehousing and Data Mining Lab | 3 | 0 | 2 | 4 |
| Professional Elective-II | 3 | 1 | 0 | 4 | |
| Professional Elective-III | 3 | 0 | 2 | 4 | |
| Open Elective-I | 3 | 0 | 0 | 3 | |
| CSE3052/ | Applied Cryptography and Network Security/ Applied Cryptography and Network Security Lab | 3 | 0 | 2 | 4 |
| CSE 3057 / CSE3057L | Neural Network and Deep Learning / Neural Network and Deep Learning | 2 | 0 | 2 | 3 |
| Total Credits | 22 | ||||
| Course Code | Course Title | L | T | P | Credits |
|---|---|---|---|---|---|
| CSE4046/ | GPU- Accelerated Data Science / GPU- Accelerated Data Science Lab | 3 | 0 | 2 | 4 |
| CSE2501 | Internet of Things | 3 | 0 | 0 | 3 |
| Professional Elective-IV | 3 | 0 | 2 | 4 | |
| Open Elective II | 3 | 0 | 0 | 3 | |
| EGR4501 | Project Phase-I | 0 | 0 | 0 | 4 |
| EGR4502 | Summer Internship | 0 | 0 | 0 | 2 |
| Total Credits | 20 | ||||
| Course Code | Course Title | L | T | P | Credits |
|---|---|---|---|---|---|
| Professional Elective-V | 3 | 0 | 2 | 4 | |
| Open Elective III | 3 | 0 | 0 | 3 | |
| EGR4503 | Project Phase-II | 0 | 0 | 0 | 10 |
| Total Credits | 17 | ||||
| Open Elective III | 3 | 0 | 0 | 3 | |
| EGR4503 | Project Phase-II | 0 | 0 | 0 | 10 |
| Total Credits | 17 | ||||
Career Path
Graduates of the programme are equipped to pursue successful careers as:
- Data Scientist Role: Data Scientists analyze and interpret complex data to help organizations make informed decisions. They use statistical methods, machine learning algorithms, and data visualization techniques to uncover patterns and insights.
- Machine Learning Engineer Role: Machine Learning Engineers design, build, and deploy machine learning models. They work on creating systems that can learn from and make predictions based on data.
- AI Research Scientist Role: AI Research Scientists conduct advanced research in artificial intelligence to develop new algorithms and technologies. They often work in academic institutions, research labs, or tech companies.
- Big Data Engineer Role: Big Data Engineers design and manage the infrastructure that allows large-scale data processing and analysis. They ensure that data pipelines are efficient and scalable.
- Business Intelligence AnalystRole: Business Intelligence Analysts use data to provide actionable insights that help businesses make strategic decisions. They create reports, dashboards, and visualizations to communicate findings.
- Data Analyst Role: Data Analysts collect, process, and perform statistical analyses on data. They help organizations understand trends, patterns, and correlations in their data.
- AI Product Manager Role: AI Product Managers oversee the development and implementation of AI-based products. They work closely with engineering, design, and marketing teams to ensure the product meets market needs.
- AI Engineers Role: AI engineer builds intelligent software applications by integrating pre-trained machine learning models and large language models (LLMs) into real-world products.
- Business Intelligence SpecialistsRole: They analyze complex business data to uncover trends and inefficiencies. By building interactive dashboards and reports, they empower organizations to optimize operations, increase profitability, and drive strategic growth.More over they also proceed for higher studies, entrepreneurial ventures, and research careers, embodying GD Goenka University’s commitment to producing globally competent professionals who leverage Artificial Intelligence and Data Science to create innovative, ethical, and socially impactful technological solutions.
Fee Structure
Yearly
| 1st Year | 2nd Year | 3rd Year | 4th Year |
|---|---|---|---|
| ₹3,60,000 | ₹3,10,000 | ₹3,10,000 | ₹3,10,000 |
Semester Wise
| 1st Sem | 2nd Sem | 3rd Sem | 4th Sem | 5th Sem | 6th Sem | 7th Sem | 8th Sem |
|---|---|---|---|---|---|---|---|
| ₹2,05,000 | ₹1,55,000 | ₹1,55,000 | ₹1,55,000 | ₹1,55,000 | ₹1,55,000 | ₹1,55,000 | ₹1,55,000 |
Eligibility Criteria
Candidates must have passed the 10+2 examination or an equivalent examination from a recognized board with Physics and Mathematics as compulsory subjects along with one of the following: Chemistry / Computer Science / Information Technology.
Obtained at least 50% marks in the above three subjects taken together.
The candidate must have passed English as a subject in the 10+2 examination.
Entrance Examination & Selection Preferability
Preference is given to merit scores achieved in national or state-level tests: IIT-JEE (Mains), State Level Entrance Exams, or the University Entrance Exam (Q-CARE).
In addition, candidates must successfully complete the Goenka Aptitude Test for Admission (GATA) and clear a Personal Interview (PI) round.
Admission Requirement
Passed 10+2 examination with Physics and Mathematics as compulsory course and any one course from Chemistry/ Computer Science/Electronics/Information Technology/ Biology/Informatics Practices/ Biotechnology/ Technical Vocational subject/ Agriculture/ Engineering Graphics/ Business Studies/Entrepreneurship.
Obtained at least 50% marks in the above 2 compulsory and any one selected (from list of 12) subjects taken together.
Passed min. 3 years Diploma examination with at least 50% marks
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