This course provides advanced study of Agentic Artificial Intelligence (AI), focusing on the design and development of AI systems that can act autonomously, adapt to dynamic environments, and achieve complex goals through reasoning, planning, and decision-making. You will explore the theoretical foundations and practical implementation of intelligent agents, including reactive, deliberative, and hybrid architectures. 

The course examines contemporary approaches to agentic behaviour, including reinforcement learning, multi-agent systems, tool-augmented large language models, and autonomous workflow orchestration. You will develop skills in designing AI agents capable of interacting with external systems, collaborating with humans and other agents, and operating safely within real-world constraints. 

Emphasis is placed on the responsible deployment of agentic AI, including considerations of transparency, alignment, safety, governance, and ethical impact. Through hands-on projects and applied case studies, you will gain experience building agent-based AI solutions for domains such as intelligent automation, robotics, decision support, and adaptive digital services. 

On completion, you will be equipped with advanced knowledge and practical expertise to contribute to emerging industry and research applications of autonomous and agent-based AI systems.