Course Requirements – What is Agentic AI and How Does it Work?

• Foundational AI Knowledge – Basic understanding of Artificial Intelligence concepts (completion of AI Basics or equivalent is recommended).

• Programming Familiarity – Prior exposure to at least one programming language (Python preferred) for understanding AI workflows and demos.

• Understanding of Machine Learning Basics – Awareness of supervised/unsupervised learning, datasets, and model training concepts will be helpful.

• Logical & Analytical Thinking – Ability to follow structured problem-solving approaches, as Agentic AI often involves reasoning and multi-step planning.

• Device & Internet Access – A laptop/desktop with stable internet to access videos, reading materials, and hands-on exercises.

• Optional (but beneficial):

  • Experience with APIs, automation tools, or workflow orchestration platforms.

  • Familiarity with cloud-based AI services (e.g., OpenAI, LangChain, or Hugging Face) to explore advanced Agentic AI implementations.

Course Description – What is Agentic AI and How Does it Work?

This course introduces learners to the emerging field of Agentic AI, a new paradigm where AI systems move beyond passive prediction to actively reason, plan, and take actions in dynamic environments. Unlike traditional AI models that respond to single prompts, Agentic AI agents can chain tasks, use tools, collaborate with other systems, and continuously adapt to achieve defined goals.

Learners will explore:

• The fundamentals of Agentic AI and how it differs from conventional AI and LLMs.

• Core components such as reasoning, memory, tool usage, and feedback loops.

• Real-world use cases across domains like customer support, workflow automation, healthcare, and finance.

• The architecture of agent frameworks, including LangChain, ReAct, and multi-agent systems.

• Ethical, security, and reliability considerations in deploying autonomous agents.

Through a mix of conceptual learning, demonstrations, and practical insights, participants will gain a strong foundation in how Agentic AI works, why it matters, and where it is heading.

Who is this for?

• AI/ML beginners who have a basic understanding of AI concepts.

• Developers, business professionals, and decision-makers exploring the next wave of AI-driven applications.

• Anyone curious about how autonomous AI agents will shape the future of work and technology.

Course Outcomes – What is Agentic AI and How Does it Work?

By the end of this course, learners will be able to:

1. Define Agentic AI – Clearly explain what Agentic AI is and how it differs from traditional AI and large language models.

2. Understand Core Components – Describe the key building blocks of Agentic AI such as reasoning, memory, planning, tool usage, and feedback loops.

3. Analyze Use Cases – Identify practical applications of Agentic AI in industries like customer service, healthcare, finance, and workflow automation.

4. Evaluate Agent Frameworks – Recognize how frameworks like LangChain, ReAct, and multi-agent systems enable the design of autonomous AI agents.

5. Demonstrate Conceptual Workflows – Illustrate how an agent can sequence tasks, interact with APIs/tools, and adapt based on outcomes.

6. Discuss Challenges & Ethics – Evaluate the risks, ethical concerns, and reliability issues associated with deploying autonomous AI systems.

7. Prepare for Hands-On Exploration – Build readiness to explore and experiment with Agentic AI tools, frameworks, and real-world implementations.