AWSDD-AAIFAWAmazon Web ServicesAW-AWSDD-AAIF1.0<p>In this course, you will learn to:</p> <ul> <li>Summarize the evolution of Agentic AI and define what makes something &quot;agentic&quot;</li><li>Identify core components of agentic systems</li><li>Distinguish between workflow, autonomous, and hybrid agents</li><li>Identify basic implementation patterns for Agentic AI</li></ul><p>We recommend that attendees of this course have:</p> <ul> <li>Generative AI Essentials or equivalent work experience</li><li>Basic AWS knowledge and software development experience</li></ul><p>This course is intended for:</p> <ul> <li>Software developers new to Agentic AI seeking foundational knowledge</li><li>Technical professionals exploring AI capabilities who are interested in core components and applications of agentic AI</li><li>Development teams evaluating Agentic AI solutions and needing to differentiate between agent types</li></ul><h5>M1: Exploring Agentic AI</h5><p>This course introduction provides anstandard level of understanding for students in the course.</p> <ul> <li>What is an AI agent?</li><li>Understanding agentic AI</li><li>Types of AI agents</li><li>Agentic AI applications</li></ul><h5>M2: Large Language Models (LLMs)</h5><p>Discuss the benefits and challenges of using agents in your workflows with LLMs.</p> <ul> <li>What are LLMS?</li><li>Understanding LLMs</li><li>How are LLMs trained?</li><li>LLM capabilities</li><li>Challenges associated with LLMs</li><li>Limitations of LLMs</li><li>Fallacy of composition</li></ul><h5>M3: Innovations powering agents</h5><p>Explore factors shaping agent development and its breadth of capabilities.</p> <ul> <li>Innovations shaping AI agents</li><li>How AI-software integration works</li><li>How chain of thought reasoning works</li><li>Impact of multimodal inference</li><li>Multi-agent collaboration</li><li>Agentic frameworks to build agents</li></ul><h5>M4: Evolution timeline</h5><p>Learn how long each phase is to take your agentic AI pipelines to production.</p> <ul> <li>Workflows to go from LLMs to agents</li><li>Evolution of gen AI models</li><li>Differences and similarities between assistants, agents, and AI systems</li></ul><h5>M5: Knowledge check + summary</h5><p>Review what was learned in the course and advise on the next steps.</p> <ul> <li>Quiz questions</li><li>Course summary</li><li>Next steps and additional resources</li></ul>In 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 AIWe recommend that attendees of this course have: - Generative AI Essentials or equivalent work experience - Basic AWS knowledge and software development experienceThis 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 typesM1: Exploring Agentic AI This course introduction provides anstandard level of understanding for students in the course. - What is an AI agent? - Understanding agentic AI - Types of AI agents - Agentic AI applications M2: 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 M3: 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 M4: 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 gen AI models - Differences and similarities between assistants, agents, and AI systems M5: Knowledge check + summary Review what was learned in the course and advise on the next steps. - Quiz questions - Course summary - Next steps and additional resources1 hour