Agentic AI Fundamentals Training introduces the core concepts behind autonomous and semi-autonomous AI systems known as AI agents. This course explains how agentic AI systems plan, reason, make decisions, and interact with tools, data, and humans to perform complex tasks. Participants will gain a strong foundation in agent-based AI thinking, real-world applications, and responsible adoption across industries.

• Understand the core concepts and architecture of Agentic AI systems
• Learn how autonomous AI agents plan, reason, and execute tasks
• Explore LLM integration, prompting, and workflow orchestration concepts
• Identify real-world use cases of Agentic AI across industries
• Gain exposure to AI agent frameworks, tools, and automation techniques
• Understand challenges, limitations, and responsible AI practices

• Business professionals and managers
• Technology and innovation teams
• AI and data enthusiasts
• Consultants and solution architects
• Students and professionals exploring agentic AI

• Basic awareness of artificial intelligence concepts
• Familiarity with digital tools and workflows
• No coding or advanced technical background required

• Understanding core principles of agentic AI
• Differentiating agents from traditional AI systems
• Designing basic agent workflows
• Identifying real-world agentic AI use cases
• Applying ethical and responsible AI practices

By the end of this training, participants will have a solid foundation in agentic AI concepts and practical understanding of how AI agents are designed, deployed, and governed. Learners will be able to identify suitable use cases, design basic agent workflows, and contribute effectively to agentic AI initiatives within their organizations.

Introduction to Agentic AI
• What is agentic AI and how it works
• Evolution from rule-based AI to autonomous agents
• Key components of an AI agent

Core Architecture of AI Agents
• Perception, reasoning, planning, and action
• Memory, tools, and environment interaction
• Single-agent vs multi-agent systems

Agent Decision-Making and Planning
• Goal-oriented behavior in agents
• Task decomposition and sequencing
• Handling uncertainty and constraints

Common Agentic AI Use Cases
• Business process automation
• Research and information retrieval
• Personal productivity and digital assistants

Human-in-the-Loop Agent Systems
• Role of human oversight and approvals
• Feedback loops and agent correction
• Trust, transparency, and accountability

Tools, Frameworks, and Ecosystems
• Overview of popular agent frameworks
• No-code and low-code agent platforms
• Integration with enterprise tools and APIs

Ethics, Safety, and Responsible Agentic AI
• Bias, hallucination, and error handling
• Data privacy and security considerations
• Governance and compliance fundamentals

Hands-on Agent Design Workshop
• Designing a simple agent workflow
• Real-world scenario simulations
• Participant exercises and feedback

• Fundamentals of Agentic AI and autonomous agents
• AI agent lifecycle and workflow orchestration
• Prompt engineering and reasoning techniques
• Tool usage and API integration concepts
• Multi-agent collaboration basics
• Real-world Agentic AI use case evaluation

• Participation in hands-on exercises
• Agent workflow design assignment
• Conceptual knowledge assessment

Participants will receive course materials, slides, reference materials, exercises and access to resources for further learning.

Participants who successfully complete the training will receive an AcadNXT Certificate in Agentic AI Fundamentals Training, validating their understanding of AI agent architectures, use cases, and responsible implementation.