Presidency School of Artificial Intelligence and Advanced Computing (PSAIAC) successfully organised a five-day Faculty Development Programme (FDP) titled "AI Beyond Boundaries: Generative Models, LLMs, and Agentic Intelligence" from 1 to 5 June 2026 at F Block Seminar Hall-02 and LSL01 Lab, Presidency University, Bengaluru.

The programme was designed to equip faculty members with advanced knowledge and practical expertise in emerging Artificial Intelligence technologies, including Generative AI, Large Language Models (LLMs), prompt engineering, and agentic AI.

The FDP featured expert sessions, hands-on demonstrations, and interactive discussions exploring modern AI architectures such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), Transformers, Vision-Language Models, autonomous AI agents, and multi-agent systems. Participants also gained exposure to leading AI frameworks, including LangChain, AutoGPT, CrewAI, and Semantic Kernel, along with their applications in education, healthcare, robotics, and intelligent automation.

The sessions were delivered by distinguished experts Dr Umarani Jayaraman, Assistant Professor, IIITDM Kancheepuram, and Dr Shailesh Sivan, Chief Technical Architect, Yours Zeros and Ones, Kerala, who shared valuable academic and industry perspectives on the rapidly evolving AI landscape.

Key Highlights

• Five-day intensive Faculty Development Programme on emerging AI technologies.
• Expert sessions led by renowned academicians and industry professionals.
• Hands-on training in Generative AI, Large Language Models (LLMs), prompt engineering, and agentic AI.
• Practical exposure to LangChain, AutoGPT, CrewAI, and Semantic Kernel.
• Interactive demonstrations showcasing AI-driven applications and intelligent systems.
• Participation of 64 faculty members from across the University.

Learning Outcomes

Participants:

• Developed a strong foundation in Generative AI and Large Language Models (LLMs).
• Learned prompt engineering techniques for AI-powered applications.
• Explored Retrieval-Augmented Generation (RAG) concepts and vector databases.
• Gained practical experience with modern AI frameworks and deployment methodologies.
• Enhanced their understanding of autonomous AI agents and multi-agent systems.
• Strengthened their research capabilities and readiness to integrate AI into teaching, learning, and innovation.

The programme successfully fostered knowledge sharing, innovation, and collaborative learning, empowering faculty members to effectively leverage cutting-edge Artificial Intelligence technologies in teaching, research, and professional practice.