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ATAL FDP JRNRV Udaipur
The ATAL FDP JRNRV Udaipur is a one-week offline training program organized by the Department of Computer Science & IT at Janardan Rai Nagar Rajasthan Vidyapeeth. Sponsored by the AICTE ATAL Academy, this face-to-face initiative focuses on AI-First Pedagogy, equipping educators to transform computer applications through Generative AI. The fully funded program offers academic certification and logistical support without requiring any registration fee. Faculty members and postgraduate students from AICTE-approved institutions located within 100 km of the host institute are eligible to apply. Interested candidates must securely submit their applications online before the scheduled sessions from 20 July 2026 to 25 July 2026.
Programme Highlights
| Organising Body | Mode | Duration | Location |
| Department of Computer Science & IT, JRNRV | Offline | One Week | JRNRV Campus, Udaipur |
About the Programme
The AICTE Training and Learning (ATAL) Academy actively imparts quality training to equip educators with sound domain knowledge and institutional leadership skills. Accordingly, the ATAL FDP JRNRV Udaipur represents a strategic effort to align technical education with the Viksit Bharat 2047 vision by fostering a robust ecosystem for Artificial Intelligence. Furthermore, the curriculum promotes inclusivity by encouraging content creation in Indian regional languages, effectively democratizing technical expertise in alignment with NEP 2020 goals.
Established in Udaipur, Janardan Rai Nagar Rajasthan Vidyapeeth (JRNRV) operates as a deemed-to-be university dedicated to societal upliftment through education. The host Department of Computer Science and Information Technology functions as a hub for technical excellence, focusing on bridging the gap between academic theory and industry requirements. Consequently, participants gain applied expertise through laboratory-based training and a mandatory industrial visit, ensuring that theoretical concepts are reliably translated into real-world applications.
Eligibility Criteria
- Academic Qualification
- Assistant Professors and Associate Professors from AICTE-approved institutions hold eligibility to apply.
- Ph.D. Scholars and postgraduate (PG) students qualify for this professional development program.
- Experience & Other Conditions
- All participants must reside within the same city or within a 100 km radius of the host institute.
- The organizing committee explicitly limits the total intake to a minimum of 30 and a maximum of 50 participants.
Benefits & Funding
This AICTE-sponsored initiative ensures broad accessibility by removing financial barriers for selected candidates.
| Component | Amount or Detail |
| Registration Fee | The registration process is completely free of cost |
| Certification | Official digital certificate awarded upon meeting attendance and comprehensive assessment criteria |
Topics / Themes Covered
- Overview of Artificial Intelligence alongside architectures for Machine Learning and Large Language Models (LLMs).
- Deep Learning frameworks including Neural Networks, NLP, and Computer Vision applications.
- Prompt Engineering techniques tailored for educators to enhance pedagogical efficiency.
- AI-driven curriculum modernization specifically designed for BCA and Computer Applications.
- Python-based AI Frameworks featuring a deep dive into TensorFlow and PyTorch.
- Mandatory implementation strategies for NEP 2020 using AI in technical education.
- Ethical AI considerations spanning bias mitigation, data privacy, and responsible deployment.
- Research methodology in AI, emphasizing the critical analysis of high-impact literature.
- AI utilized in assessment design, including automated grading and evaluation frameworks.
- Future trends focusing on Quantum AI and Next-Gen Communication integration.
Selection Process
- The official document does not detail an initial application screening process; candidates must register via the ATAL portal.
- To secure certification, candidates undergo an MCQ or reasoning assessment carrying a 10% weightage.
- Participants must maintain a minimum of 80% attendance to earn a 20% evaluation weightage.
- Teams must submit an article summary contributing to a 30% evaluation weightage.
- Evaluators grade the output of practical lab sessions for a 15% weightage.
- Attendees must compile an industrial visit report holding a 10% weightage.
- Participants submit a reflection journal contributing the final 15% evaluation weightage.
How to Apply
- Navigate directly to the official AICTE ATAL portal.
- Complete the mandatory registration process using accurate academic and residential details to confirm the 100 km radius requirement.
- Select the corresponding JRNRV Udaipur program and securely submit your application.
Important Dates
| Event | Date |
| Programme Start Date | 20-07-2026 |
| Programme End Date | 25-07-2026 |
Important Links
| Resource | Link |
| Apply Online | Click Here |
| Download FDP Brochure | Download |
| Download FDP Schedule | Download |
Contact Details
- Coordinator: Dr. Chandresh Kumar Chhatlani (Associate Professor, Dept. of CS & IT)
- Email: atalfdp@jrnrvu.edu.in
- Phone No: 0294-2492440, 09928544749, 09882785752
- Official Address: Department of Computer Science & IT, Janardan Rai Nagar Rajasthan Vidyapeeth (Deemed to be University), Airport Road, Pratap Nagar, Udaipur (Raj.)
FAQs
Q1: Who is eligible to participate in the ATAL FDP JRNRV Udaipur?
A1: Assistant Professors, Associate Professors, Ph.D. scholars, and PG students from AICTE-approved institutions located within 100 km of the host institute are eligible.
Q2: Is there any registration fee for this training program?
A2: No, registration for this program is completely free of cost via the AICTE ATAL Portal.
Q3: What are the main topics covered during the training?
A3: The curriculum covers generative AI, deep learning, prompt engineering, Python-based frameworks (TensorFlow/PyTorch), and AI-driven curriculum modernization.
Q4: Will the program provide practical or industrial exposure?
A4: Yes, the six-day schedule includes daily hands-on training labs and a mandatory industrial visit to bridge the gap between theory and real-world application.
Q5: How will candidates be evaluated for the final certificate?
A5: Participants must achieve 70% marks across a combined assessment that includes attendance, an MCQ test, a team article summary, lab outputs, an industrial visit report, and a reflection journal.