Course Description
Short Course | 18 hours | 1.8 CEUs | $2,295This course provides a hands-on introduction to the foundational concepts of agentic systems and how they extend generative AI (GenAI) to build intelligent agents that can plan, reason, and act autonomously using large language models and supporting architectures. Students will explore how AI agents operate independently, make decisions, and leverage tools to complete complex, multi-step tasks. Beginning with the fundamentals of generative AI and agent architecture, the course follows a structured, session-based format covering core principles such as agent components, reflection and introspection, tool use, planning, and multi-agent coordination. Through guided instruction, learners will gain a clear understanding of how agentic systems are built and how they operate in real-world scenarios.
AI410 is the second course in the Agentic AI and Retrieval Augmented Generation (RAG) Certificate. To complete the certificate students will also enroll in AI400. Click on each course link for more details and to add to cart.
Course Outline
Session 1: Fundamentals of Generative AI
- Overview of generative AI concepts and models
- Role of Generative AI in agentic systems
- Applications and limitations
Session 2: Principles of Agentic Systems
- Agency, autonomy, and self-governance
- Agent architectures and characteristics
- Introduction to multi-agent systems
Session 3: Essential Components of Intelligent Agents
- Knowledge representation and reasoning
- Learning and decision-making
- Planning concepts in agents
Session 4: Reflection and Introspection in Agents
- Self-evaluation and meta-reasoning
- Improving decision-making through feedback
Session 5: Enabling Tool Use and Planning Agents
- Tool use and function calling
- Planning and execution of tasks
Session 6: Coordinator, Worker, and Delegator Approach
- Multi-agent coordination
- Roles and collaboration between agents
- Task delegation and workflows
Learner Outcomes
- Explain how agentic systems extend generative AI
- Describe how AI agents plan, reason, and act
- Identify key components of intelligent agents
- Understand how agents use tools and execute tasks
- Explain multi-agent coordination approaches
- Recognize real-world applications of agentic systems
Prerequisites
- General awareness of AI or large language model or completion of Artificial Intelligence and Large Language Models Foundations (AI390)
- General awareness of Retrieval Augmented Generation (RAG) or completion of Retrieval-Augmented Generation (RAG) (AI400)
- No prior experience with agentic systems required
Duration
18 Hours | 3 Days or 6 NightsEnroll Now - Select a section to enroll in
*Academic Unit eligibility to be determined by college/university in which you are enrolled in a degree seeking program.