{"course":{"productid":36717,"modality":1,"active":true,"language":"en","title":"AWS Discovery Day: Agentic AI Foundations","productcode":"AWSDD-AAIF","vendorcode":"AW","vendorname":"Amazon Web Services","fullproductcode":"AW-AWSDD-AAIF","courseware":{"has_ekit":true,"has_printkit":false,"language":""},"url":"https:\/\/portal.flane.ch\/course\/amazon-awsdd-aaif","objective":"<p>In this course, you will learn to:<\/p>\n<ul>\n<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>","essentials":"<p>We recommend that attendees of this course have:<\/p>\n<ul>\n<li>Generative AI Essentials or equivalent work experience<\/li><li>Basic AWS knowledge and software development experience<\/li><\/ul>","audience":"<p>This course is intended for:<\/p>\n<ul>\n<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>","contents":"<h5>M1: Exploring Agentic AI<\/h5><p>This course introduction provides anstandard level of understanding for students in the course.<\/p>\n<ul>\n<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>\n<ul>\n<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>\n<ul>\n<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>\n<ul>\n<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>\n<ul>\n<li>Quiz questions<\/li><li>Course summary<\/li><li>Next steps and additional resources<\/li><\/ul>","summary":"<p>In this course, you&rsquo;ll explore the core principles and strategies to consider when designing Agentic AI systems on AWS. You&rsquo;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.<\/p>","objective_plain":"In this course, you will learn to:\n\n\n- Summarize the evolution of Agentic AI and define what makes something \"agentic\"\n- Identify core components of agentic systems\n- Distinguish between workflow, autonomous, and hybrid agents\n- Identify basic implementation patterns for Agentic AI","essentials_plain":"We recommend that attendees of this course have:\n\n\n- Generative AI Essentials or equivalent work experience\n- Basic AWS knowledge and software development experience","audience_plain":"This course is intended for:\n\n\n- Software developers new to Agentic AI seeking foundational knowledge\n- Technical professionals exploring AI capabilities who are interested in core components and applications of agentic AI\n- Development teams evaluating Agentic AI solutions and needing to differentiate between agent types","contents_plain":"M1: Exploring Agentic AI\n\nThis course introduction provides anstandard level of understanding for students in the course.\n\n\n- What is an AI agent?\n- Understanding agentic AI\n- Types of AI agents\n- Agentic AI applications\nM2: Large Language Models (LLMs)\n\nDiscuss the benefits and challenges of using agents in your workflows with LLMs.\n\n\n- What are LLMS?\n- Understanding LLMs\n- How are LLMs trained?\n- LLM capabilities\n- Challenges associated with LLMs\n- Limitations of LLMs\n- Fallacy of composition\nM3: Innovations powering agents\n\nExplore factors shaping agent development and its breadth of capabilities.\n\n\n- Innovations shaping AI agents\n- How AI-software integration works\n- How chain of thought reasoning works\n- Impact of multimodal inference\n- Multi-agent collaboration\n- Agentic frameworks to build agents\nM4: Evolution timeline\n\nLearn how long each phase is to take your agentic AI pipelines to production.\n\n\n- Workflows to go from LLMs to agents\n- Evolution of gen AI models\n- Differences and similarities between assistants, agents, and AI systems\nM5: Knowledge check + summary\n\nReview what was learned in the course and advise on the next steps.\n\n\n- Quiz questions\n- Course summary\n- Next steps and additional resources","summary_plain":"In this course, you\u2019ll explore the core principles and strategies to consider when designing Agentic AI systems on AWS. You\u2019ll learn how Agentic AI differs from traditional conversational systems, and how using agents helps build autonomous, goal-driven solutions that solve real-world problems.","version":"1.0","duration":{"unit":"d","value":0,"formatted":"1 hour"},"lastchanged":"2026-03-20T17:50:00+01:00","parenturl":"https:\/\/portal.flane.ch\/swisscom\/en\/json-courses","nexturl_course_schedule":"https:\/\/portal.flane.ch\/swisscom\/en\/json-course-schedule\/36717","source_lang":"en","source":"https:\/\/portal.flane.ch\/swisscom\/en\/json-course\/amazon-awsdd-aaif"}}