AWS Discovery Day: Agentic AI Foundations
- Course Code GKAWS-DDAAF
- Duration 1 day
Course Delivery
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Course Delivery
This course is available in the following formats:
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Company Event
Event at company
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Public Classroom
Traditional Classroom Learning
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Virtual Learning
Learning that is virtual
Request this course in a different delivery format.
Course Overview
TopIn this course, you’ll explore the core principles and strategies to consider when designing Agentic AI systems on AWS.
You’ll learn how Agentic AI differs from traditional conversational systems, and how using agents helps build autonomous, goal-driven solutions that solve real-world problems.
Updated August 2026
Course Schedule
TopTarget Audience
TopThis course is intended for:
- Software developers new to Agentic AI seeking foundational knowledge
- Technical professionals exploring AI capabilities who are interested in core components and applications of agentic AI
- Development teams evaluating Agentic AI solutions and needing to differentiate between agent types
Course Objectives
TopIn this course, you will learn to:
- Summarize the evolution of Agentic AI and define what makes something "agentic"
- Identify core components of agentic systems
- Distinguish between workflow, autonomous, and hybrid agents
- Identify basic implementation patterns for Agentic AI
Course Content
TopModule 1: Exploring Agentic AI
This course introduction provides a standard level of understanding for students in the course.
- What is an AI agent?
- Understanding agentic AI
- Types of AI agents
- Agentic AI applications
Module 2: Large Language Models (LLMs)
Discuss the benefits and challenges of using agents in your workflows with LLMs.
- What are LLMs?
- Understanding LLMs
- How are LLMs trained?
- LLM capabilities
- Challenges associated with LLMs
- Limitations of LLMs
- Fallacy of composition
Module 3: Innovations Powering Agents
Explore factors shaping agent development and its breadth of capabilities.
- Innovations shaping AI agents
- How AI-software integration works
- How chain-of-thought reasoning works
- Impact of multimodal inference
- Multi-agent collaboration
- Agentic frameworks to build agents
Module 4: Evolution Timeline
Learn how long each phase is to take your agentic AI pipelines to production.
- Workflows to go from LLMs to agents
- Evolution of generative AI models
- Differences and similarities between assistants, agents, and AI systems
Module 5: Knowledge Check and Summary
Review what was learned in the course and advise on the next steps.
- Quiz questions
- Course summary
- Next steps and additional resources
Course Prerequisites
TopWe recommend that attendees of this course have:
- Generative AI Essentials or equivalent work experience
- Basic AWS knowledge and software development experience
Test Certification
TopNone
Follow on Courses
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