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About the University
Jaipur National University, Jaipur is one of the top self-financed private university in Rajasthan sponsored by the Mahima Shiksha Samiti.
Innovation and Incubation
If you have an innovative idea, we can show you the way ahead. Be an entrepreneur with the perfect..
Social Impact/CSR
Social responsibility takes many forms - from providing affordable/free healthcare...
Why JNU?
Their focus is to develop both education and critical skills to help our students excel in life.
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- Academics
Schools
- School of Engineering & Technology
- School of Business & Management
- School of Computer & Systems Sciences
- School of Education
- School of Languages, Literature and Society
- School of Life & Basic Sciences
- School of Pharmaceutical Sciences
- School of Media Studies
- School of Fashion Design
- Seedling School of Law and Governance
- Seedling School of Nursing
- School of Allied Health Sciences
- School of Agricultural Sciences
- School of Hotel Management & Catering Technology
- Jaipur National University Institute for Medical Sciences and Research Centre
- Research
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Enriching the Intellect
Inspire Your Essence
Outside the classroom
Adapt to Physical Wellness
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Admission HelpDesk
B.Tech AI & DS (Artificial Intelligence and Data Science) - In collaboration with Coding Pro
School of Engineering & Technology
APPLY ONLINE-
Duration
4 Years
-
Eligibility
50% Aggregate in 10+2 with Physics and Mathematics as Compulsory Subjects.
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Selection Procedure
Entrance Test + PI
Program Outcomes
Cognitive Knowledge
Provide education that builds a strong foundation in Artificial Intelligence, Data Science, statistics, and core Computer Science principles for analyzing and solving complex data-driven problems.
Information and Computer Literacy
Equip students with up-to-date knowledge of programming, data analysis tools, databases, and AI technologies, along with the ability to effectively use digital resources and scientific literature.
Employability Skills
Enhance employability by enabling students to analyze large datasets, build data-driven models, and develop intelligent solutions for real-world applications across industries.
Experimental Skills
Provide hands-on training in data collection, preprocessing, visualization, and implementation of AI and data science models using modern tools and platforms.
Research Skills
Develop the ability to apply research methodologies, design experiments, analyze and interpret data, and generate meaningful insights and innovations in AI and Data Science.
Critical Thinking
Empower students to critically analyze data, identify patterns, evaluate different approaches, and make informed decisions based on data-driven insights.
Professional Ethics
Instill ethical values related to data usage, privacy, security, and responsible AI practices, ensuring transparency and accountability in decision-making.
Life-long Learning
Encourage continuous learning and adaptability to emerging trends in AI, big data, and analytics, enabling graduates to stay relevant in a rapidly evolving technological landscape.
Career Paths
Data Scientist
Data Analyst
Business Intelligence Developer
Data Engineer
Big Data Engineer
Data Visualization Specialist
Statistician
Quantitative Analyst
Data Consultant
Power BI Developer
Curriculum
| S. No. | Course Category | Course Name | Credits |
|---|---|---|---|
| 1 | ESC | Engineering Graphics and Visualization | 2 |
| 2 | BSC | Engineering Physics | 4 |
| 3 | BSC | Engineering Mathematics I | 4 |
| 4 | ESC | Engineering Graphics and Visualization lab | 1 |
| 5 | BSC | Engineering Physics (Semiconductor Physics) lab | 1 |
| 6 | ESC | Programming for Problem Solving using C | 3 |
| 7 | ESC | Programming for Problem Solving using C lab | 1 |
| 8 | ESC | Basic Electrical Engineering | 3 |
| 9 | ESC | Basic Electrical Engineering lab | 1 |
| 10 | MC | Environmental Science | 1 |
| 11 | HSMC | Communication Skills | 2 |
| 12 | Audit | Digital Presentation skills lab | 0 |
| Total | 23 | ||
| S. No. | Course Category | Course Name | Credits |
|---|---|---|---|
| 1 | BSC | Biology for Engineers | 4 |
| 2 | BSC | Biology for Engineers lab | 1 |
| 3 | BSC | Engineering Mathematics II (Probability & Statistics) | 4 |
| 4 | HSMC | Financial Data Analysis | 2 |
| 5 | SEC | Design Thinking | 1 |
| 6 | SEC | Design Thinking & Idea Lab | 1 |
| 7 | ESC | Python Programming | 3 |
| 8 | ESC | Python Programming lab | 1 |
| 9 | ESC | Digital Electronics | 3 |
| 10 | ESC | Digital Electronics Lab | 1 |
| 11 | VAC | Climate Change and Green Technology | 1 |
| 12 | Audit | Universal Human Values | 0 |
| Total | 22 | ||
| S. No. | Course Category | Course Name | Credits |
|---|---|---|---|
| 1 | PCC | Discrete Mathematical Structure | 3 |
| 2 | PCC | Data Structures and Algorithm | 3 |
| 3 | PCC | Data Structures and Algorithm lab | 1 |
| 4 | ESC | Introduction to AI | 3 |
| 5 | ESC | Introduction to AI lab | 1 |
| 6 | PCC | Object Oriented Programming using C++ | 3 |
| 7 | PCC | Object Oriented Programming using C++ lab | 1 |
| 8 | PCC | Computer Organization and Architecture | 3 |
| 9 | VAC | Indian Knowledge System | 1 |
| 10 | SEC | E-Commerce & Digital Business | 2 |
| 11 | HSMC | Technical writting | 2 |
| Total | 23 | ||
| S. No. | Course Category | Course Name | Credits |
|---|---|---|---|
| 1 | PCC | Operating Systems | 3 |
| 2 | PCC | Operating Systems lab | 1 |
| 3 | PCC | Database Management Systems | 3 |
| 4 | PCC | Database Management Systems lab | 1 |
| 5 | PCC | Computer Networks | 3 |
| 6 | PCC | Computer Networks lab | 1 |
| 7 | BSC | Vector Calculus | 3 |
| 8 | PCC | Machine Learning | 4 |
| 9 | PCC | Machine learning Lab | 1 |
| 10 | SEC | Introduction to UI/UX | 2 |
| 11 | SEC | Introduction to UI/UX Lab | 1 |
| 12 | OEC | Open Elective I | 2 |
| Total | 25 | ||
| S. No. | Course Category | Course Name | Credits |
|---|---|---|---|
| 1 | PCC | Web Technology | 3 |
| 2 | PCC | Web Technology lab | 1 |
| 3 | PCC | R Programming | 3 |
| 4 | PCC | Deep Learning | 3 |
| 5 | PCC | Deep Learning lab | 1 |
| 6 | PCC | Data Science | 3 |
| 7 | PCC | Data Science lab | 1 |
| 8 | BSC | Linear Algebra | 3 |
| 9 | SEC | Startup Creation and Policies | 2 |
| 10 | PEC | Elective I Quantum Computing Cloud AI |
3 |
| Total | 23 | ||
| S. No. | Course Category | Course Name | Credits |
|---|---|---|---|
| 1 | PCC | Data Mining and Warehousing | 4 |
| 2 | PCC | Data Mining and Warehousing lab | 1 |
| 3 | PCC | Statistical Learning & Bayesian Methods | 4 |
| 4 | PCC | Data Engineering | 3 |
| 5 | PCC | Data Engineering lab | 1 |
| 6 | PCC | Predictive Modeling & Time Series | 3 |
| 7 | PCC | Predictive Modeling & Time Series lab | 1 |
| 8 | PCC | Systems Thinking and Design | 2 |
| 9 | PEC | Elective II Explainable AI & AI Ethics AI For data processing |
3 |
| 10 | OEC | Open Elective II | 2 |
| 10 | SEC | Minor Project | 3 |
| Total | 27 | ||
| S. No. | Course Category | Course Name | Credits |
|---|---|---|---|
| 1 | PCC | Big Data Analytics | 4 |
| 2 | PCC | Big Data Analytics lab | 1 |
| 3 | PCC | Computer Vision and Image Processing | 4 |
| 4 | PCC | Computer Vision and Image Processing lab | 1 |
| 5 | SEC | Capstone Project | 3 |
| 6 | PCC | Data Analysis Using Python | 3 |
| 7 | PCC | Data Analysis Using Python lab | 1 |
| 8 | PEC | Elective III Health Care Analytics AI Driven Blockchain System |
3 |
| 9 | PEC | Elective IV Inferential Statistics AI in IoT & Smart Systems |
3 |
| Total | 23 | ||
| S. No. | Course Category | Course Name | Credits |
|---|---|---|---|
| 1 | Project/ Internship | Industrial Internship/Dissertation (AI Based) | 8 |
| 3 | Open Elective | Open Elective - III (MOOC) | 2 |
| 4 | Open Elective | Open Elective - IV (MOOC) | 2 |
| Total | 12 | ||
Tuition Fee
₹1,51,840
Note
*Lab & Library fee will be charged separately
#Program Proposed from Session 2026-27
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