OPEN HOUSE 2026 Click here
OPEN HOUSE 2026 Click here
From Models to Agents: An introduction to Agentic Deep Learning
Organizers |
Faculty of Engineering & Technology |
Participants |
95 |
Contact No. |
|
Start Date |
21/02/2026 08:00 AM |
End Date |
21/02/2026 09:00 AM |
Venue |
Ganpat University |
Social Media Share |
Description
The Ganpat University – Institute of Computer Technology (GUNI–ICT) organized Emerging Technologies Lecture Series on “From Models to Agents: An introduction to Agentic Deep Learning” on 21st February, 2026 from 08:00 AM to 09:00 AM. The session was organized with the objective of enhancing awareness about Agentic AI and Deep Learning.
The Emerging Technologies Lecture Series was efficiently inaugurated by Dr. Rohit Patel, Principal, GUNI-ICT and coordinated by Prof. Tejas Kadiya and Prof. Umesh Lakhtariya, whose efforts ensured smooth planning and successful execution of the Lecture Series.
Session Highlights:
As part of the Emerging Technologies Lecture Series, an expert lecture titled “From Models to Agents: An Introduction to Agentic Deep Learning” was delivered by Mr. Palwinder Singh for students. The session aimed to introduce participants to the evolving paradigm of agentic AI systems and their significance in modern artificial intelligence research and applications.
- Introduction to the concept of Agentic Deep Learning and its distinction from traditional deep learning models.
- Explanation of how AI systems transition from passive prediction models to autonomous, goal-driven agents.
- Discussion on core components of agentic systems such as perception, decision-making, memory, and action.
- Overview of real-world applications including autonomous systems, intelligent assistants, robotics, and decision-support systems.
- Insights into current research trends and future directions in agentic AI.
- Interactive discussion session addressing participant queries and research interests.
Key Outcomes:
- Students Participants gained foundational understanding of Agentic Deep Learning concepts.
- Enhanced awareness of emerging AI paradigms beyond conventional model-centric approaches.
- Improved clarity on research and application opportunities in agent-based AI systems.
- Motivation for students to explore advanced AI topics and interdisciplinary research.
- Strengthened engagement with emerging technologies under the lecture series.
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