Agentic AI Builder (Exam AGB-110): Setting Up a Functional AI Agent Courseware (CNX0026SE)
Your organization has assessed its need and ability to implement one or more AI agents with minimal risk. Now it's just a matter of building those agents—that's where you come in. In this course, you'll translate business requirements into a functional AI agent that can automate complex tasks and processes that would otherwise require significant human effort. Ultimately, this can lead to improved user productivity, a reduction in operational costs, and enhanced employee and customer satisfaction.
This is the second course in a series and is meant to build upon the foundation of the first course by giving technical practitioners the skills they need to successfully build agentic AI into their organizations.
Benefits
In this course, you will build an AI agent from scratch that can automate important tasks requiring some level of human-like judgment.
- Set up the agent development environment.
- Assess LLM behavior in agent contexts.
- Implement the agent reasoning loop.
- Implement tools for an agent to use.
- Add knowledge to an agent through retrieval-augmented generation (RAG).
- Enforce structure, safety, and reliability in an agent.
- Test the behavior and performance of an agent.
- Deploy a single-agent system to production.
Teaching This Course
The publisher has provided details here on how to teach this Agentic AI Builder (Exam AGB-110): Setting Up a Functional AI Agent course.
Outline
- Lesson 1: Setting Up the Agent Development Environment
- Topic A: Configure a Python-Based Agent Workspace
- Topic B: Configure LLM Access
- Topic C: Configure Runtime Constraints
- Lesson 2: Assessing LLM Behavior in Agent Contexts
- Topic A: Analyze LLM Capabilities and Limitations
- Topic B: Design Prompts for Agent Reasoning
- Lesson 3: Implementing the Agent Reasoning Loop
- Topic A: Implement the ReAct Pattern
- Topic B: Manage Agent State Across Iterations
- Topic C: Manage Memory and Persistence
- Lesson 4: Using Agent Tools
- Topic A: Design Agent Tools and Interfaces
- Topic B: Execute and Validate Tool Calls
- Lesson 5: Adding Knowledge with Retrieval-Augmented Generation
- Topic A: Implement Document Ingestion and Embeddings
- Topic B: Retrieve and Use Context Effectively
- Lesson 6: Enforcing Structure, Safety, and Reliability in an Agent
- Topic A: Enforce Structured Outputs
- Topic B: Handle Uncertainty and Failures
- Lesson 7: Testing an Agent
- Topic A: Monitor Agent Behavior
- Topic B: Evaluate Agent Performance
- Topic C: Analyze an Agent for Security Flaws
- Lesson 8: Deploying a Single-Agent System
- Topic A: Expose Agent Interfaces
- Topic B: Review Readiness and Limitations
Required Prerequisites
To ensure your success in this course, you should have foundational knowledge of agentic AI, including concepts like agentic frameworks, large language models (LLMs), tokens, context windows, agentic tools, retrieval-augmented generation (RAG), behavioral guardrails, and more. You can obtain this level of knowledge by taking the CertNexus AgenticAIBIZ™ (Exam AGZ-110): Foundations of Agentic AI course.
You must also have proficiency using at least one programming language. This course primarily uses Python® to illustrate agentic concepts, so experience with Python is recommended. Logical Operations provides the following courses that teach both Python and general programming skills:
- Introduction to Programming with Python® (Second Edition)
- Advanced Programming Techniques with Python® (Second Edition)
License
Length: 3 days | $157.50 per copy
What is Included?
- Student Manual
- Student Class Files
- Extra Trainer Files
- PowerPoint Presentation
