CONTENTS OF THE WORKSHOP

• Explores the foundations of Generative AI— from tokenization, transformers, and inference to AI agents, tool integration, and building simple LLM-based systems—along with their limitations and scaling principles. It redefines quality in education and research through AI-augmented learning, innovation with large models, and the ethical responsibilities tied to academic and intelligent systems.
• Overall, it highlights AI as a transformational force driving intelligent automation, smart innovation ecosystems, AI-assisted decision-making, and diverse applications across education, healthcare, research, and beyond.