Agentic AI Essentials Training provides a comprehensive foundation in AI systems that can plan, reason, act, and collaborate autonomously. This course explains the core principles behind agentic AI, how agent-based systems differ from traditional AI models, and how organizations can apply agentic AI for automation, decision support, and complex workflows. The training is framework-agnostic while referencing modern agent platforms used in real-world implementations.

• Understand fundamentals of Agentic AI
• Identify components of AI agents and workflows
• Use LLMs with tools, memory, and reasoning
• Design simple autonomous AI agents
• Apply AI agents in business use cases

• Business and technology professionals
• AI and automation teams
• Product managers and innovation leaders
• Consultants and solution designers
• Professionals exploring autonomous AI systems

• Basic understanding of artificial intelligence concepts
• Familiarity with workflows or problem-solving processes
• No programming or advanced AI background required

• Understanding agentic AI concepts and architectures
• Designing goal-driven AI agents
• Managing agent autonomy, reasoning, and actions
• Applying agentic AI to business and operational use cases
• Evaluating risks and responsible AI deployment

By the end of this training, participants will be able to understand, design, and evaluate agentic AI systems. Learners will gain the confidence to identify suitable use cases, design agent-driven workflows, and apply agentic AI responsibly across business and professional environments.

Introduction to Agentic AI
• What is agentic AI and why it matters
• Differences between generative AI and agentic systems
• Real-world examples of agentic AI

Core Components of Agentic AI Systems
• Goals, planning, and reasoning
• Memory, tools, and environment interaction
• Feedback loops and iteration

Types of AI Agents
• Reactive, deliberative, and hybrid agents
• Single-agent vs multi-agent systems
• Role-based and collaborative agents

Agent Design Fundamentals
• Defining objectives and constraints
• Managing context and state
• Ensuring reliable agent behavior

Agentic AI Workflows and Automation
• Task decomposition and sequencing
• Decision-making and conditional logic
• Human-in-the-loop agent workflows

Business and Enterprise Applications
• Agentic AI for automation and operations
• Research, analysis, and decision support
• Cross-functional enterprise use cases

Governance, Ethics, and Risk Management
• Bias, accuracy, and hallucination risks
• Data privacy and security considerations
• Responsible and compliant AI adoption

Hands-on Practice and Case Studies
• Agent workflow design exercises
• Real-world agentic AI scenarios
• Participant practice and feedback

• Basics of Agentic AI
• Agent architecture and lifecycle
• Prompting and reasoning techniques
• Tool integration and automation
• Real-world agent use cases

• Participation in hands-on exercises
• Agent workflow design assignment
• Knowledge-based assessment

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

Participants who successfully complete the training and evaluation will receive an AcadNXT Certificate of Completion in Agentic AI Essentials Training, recognizing their foundational expertise in autonomous AI systems.