Opleiding: Agentic AI Mastery

Agentic AI Mastery.

The Agentic AI Mastery Training: LearningKit prepares professionals to build the next generation of intelligent AI systems that can reason, plan, collaborate, and act autonomously in dynamic business environments.

This comprehensive LearningKit combines the theoretical foundations of Agentic AI with practical implementation techniques used by leading AI development teams. You'll explore agent architectures, cognitive workflows, memory systems, reasoning strategies, feedback mechanisms, reusable design patterns, and governance considerations that enable responsible autonomous AI development.

Practical implementation is a core focus throughout the training. You'll learn how to build intelligent applications using LangChain, integrate Retrieval-Augmented Generation (RAG) for knowledge-grounded responses, and create robust state-driven workflows with LangGraph. These technologies allow you to develop AI agents that use external tools, manage complex workflows, collaborate across multiple agents, and operate with greater transparency and reliability.

Ideal for AI developers, machine learning engineers, enterprise architects, software engineers, and technical decision-makers, this LearningKit provides the expertise required to design, implement, and scale secure, explainable, and production-ready Agentic AI solutions for modern organizations.

This LearningKit with more than 5 hours of learning is divided into three tracks:

Course Outcome

Track 1: Agentic AI - Foundations, Architectures, and Frameworks

Build a strong conceptual and architectural foundation for agentic AI systems, including autonomy, perception, reasoning, memory, feedback, adaptation, frameworks and reusable design patterns.

• Inside Agentic AI: Foundations and Frontiers
• Inside Agentic AI: Core Architecture of Agentic Systems
• Inside Agentic AI: Popular Frameworks
• Agentic AI Design Patterns: Reusable Blueprints for Smarter Systems

Inside Agentic AI: Foundations and Frontiers

Course: 40 Minutes

• Course Overview
• What Makes AI Agentic?
• Core Properties of Agentic AI Systems
• Knowledge Check: Reviewing the Core Properties of Agentic AI Systems
• Inside the Agentic Loop
• Knowledge Check: Assessing Information Flow in Agentic AI Systems
• Step-by-Step Agentic Flow: Case Study
• Where Agents Come Alive: Real-World Applications
• Limitations and Risks of agentic AI
• Course Summary

Inside Agentic AI: Core Architecture of Agentic Systems

Course: 35 Minutes

• Course Overview
• How Agentic AI Systems Think and Act: A Visual Walkthrough
• Knowledge Check: Understanding the Agentic AI Loop: From Perception to Feedback
• Perception: Understanding Inputs Intelligently
• Knowledge Check: Identifying How Agents Prepare for Planning
• How Agentic AI Systems Use Memory
• Knowledge Check: Understanding How Memory Contributes to Learning
• Planning with Agentic AI Systems
• Using Tools with Agentic AI
• Knowledge Check: Identifying How Agentic AI Selects Task-Relevant Tools
• Agentic AI and Environmental Integration
• How Agentic AI Systems Improve Over Time
• Reactive, Deliberative, and Learning-Based Architectures
• Course Summary

Inside Agentic AI: Popular Frameworks

Course: 33 Minutes

• Course Overview
• LangChain: Backbone of Custom AI Agents
• LangGraph: Structured Multi-Agent Workflows
• Knowledge Check: Identifying LangGraph Agent Workflows
• AutoGen: Simplified Multi-Agent Collaboration
• Knowledge Check: Reviewing AutoGen for Multi-Agent Setups
• CrewAI: Structured Role-Based Agent Collaboration
• Knowledge Check: Identifying Role-Based Agent Workflows in CrewAI
• LlamaIndex: Connecting Agents to External Knowledge
• Knowledge Check: Reviewing How LlamaIndex Enhances Workflows
• Haystack: Modular RAG Pipelines
• Knowledge Check: Reviewing Haystack's Support for Building Pipelines
• n8n: No-Code Automation for Agent Actions
• Course Summary

Agentic AI Design Patterns: Reusable Blueprints for Smarter Systems

Course: 49 Minutes

• Course Overview
• Why Design Patterns Matter in Agentic System
• Agentic Pattern Anatomy: Trigger, Flow, Feedback, and Role
• The ReAct Loop: Reasoning + Action + Feedback
• Knowledge Check: Identifying When Not to Use ReAct: Pattern Limitations
• Reflex Agents vs. Deliberative Agents
• Chain-of-Thought and Tree-of-Thought Patterns
• Knowledge Check: Identifying Characteristics of Chain-of-Thought Reasoning
• Role-Based Agent Collaboration
• Multi-Agent Task Routing and Arbitration
• Feedback-Driven Agent Loops
• Agentic AI: Reflection and Self-Critique Patterns
• Course Summary

Assessment:

• Final Exam: Agentic AI - Foundations, Architectures, and Frameworks

Track 2: Agentic AI in Action

Apply agentic AI concepts in practice with LangChain, RAG and LangGraph to build tool-enabled agents, memory-aware chatbots, controlled workflows and scalable agentic systems.

• Agentic AI in Action: Hands-On with LangChain
• Agentic AI in Action: Tool Use with LangChain
• RAG with LangChain: Foundations to Practice
• Agentic AI in Action: Controlled Workflows with LangGraph

Agentic AI in Action: Hands-On with LangChain

Course: 20 Minutes

• Course Overview
• Applying a Simple Chain with Gemini
• Designing Prompt Templates and Constructing SequentialChains in LangChain
• Implementing a Basic Chatbot Without Memory in LangChain
• Integrating ConversationBufferMemory to Enhance Chatbots
• Differentiating Context with ConversationBufferWindowMemory
• Course Summary

Agentic AI in Action: Tool Use with LangChain

Course: 31 Minutes

• Course Overview
• Building a Calculator Tool in LangChain
• Using Built-In Tools in LangChain: Search and Wikipedia
• Creating a Custom Weather Tool in LangChain
• Combining Multiple Tools in LangChain Agents
• Course Summary

RAG with LangChain: Foundations to Practice

Course: 1 Hour, 4 Minutes

• Course Overview
• RAG Essentials: Why We Need It?
• Knowledge Check: Assessing the Fundamentals of RAG
• Anatomy of a RAG Pipeline
• Knowledge Check: Identifying the Anatomy of a Rag Pipeline
• RAG with LangChain
• Knowledge Check: Evaluating How RAG Integrates with LangChain
• Preparing Data and Retrieval for a RAG System in LangChain
• Connecting the Language Model and Building the Complete RAG Pipeline
• Knowledge Check: Assessing How to Build a RAG Pipeline in LangChain
• Building a Conversational RAG System with LangChain
• Knowledge Check: Evaluating How to Build a Conversational RAG System Using LangChain
• Implementing Multi-Source RAG
• Course Summary

Agentic AI in Action: Controlled Workflows with LangGraph

Course: 1 Hour, 2 Minutes

• Course Overview
• LangGraph Core Concepts
• Understanding State Flow
• Knowledge Check: Reviewing How State Flows in LangGraph
• Understanding LangGraph Workflow Patterns
• How Conditional Routing Works
• Knowledge Check: Reviewing How Conditional Routing Works
• Building Your First StateGraph1
• Building Conditional Edges and Branching Logic in LangGraph
• Testing and Running Your Conditional Routing Workflow
• Course Summary

Assessment:

• Final Exam: Agentic AI in Action

Specificaties
Taal: Engels
Kwalificaties van de Instructeur: Gecertificeerd
Cursusformaat en Lengte: Lesvideo's met ondertiteling, interactieve elementen en opdrachten en testen
Lesduur: 5:34 uur
Assesments: De assessment test uw kennis en toepassingsvaardigheden van de onderwerpen uit het leertraject. Deze is 365 dagen beschikbaar na activering.
Online Virtuele labs: Ontvang 12 maanden toegang tot virtuele labs die overeenkomen met de traditionele cursusconfiguratie. Actief voor 365 dagen na activering, beschikbaarheid varieert per Training.
Online mentor: U heeft 24/7 toegang tot een online mentor voor al uw specifieke technische vragen over het studieonderwerp. De online mentor is 365 dagen beschikbaar na activering, afhankelijk van de gekozen Learning Kit.
Voortgangsbewaking: Ja
Toegang tot Materiaal: 365 dagen
Technische Vereisten: Computer of mobiel apparaat, Stabiele internetverbindingen Webbrowserzoals Chrome, Firefox, Safari of Edge.
Support of Ondersteuning: Helpdesk en online kennisbank 24/7
Certificering: Certificaat van deelname in PDF formaat
Prijs en Kosten: Cursusprijs zonder extra kosten
Annuleringsbeleid en Geld-Terug-Garantie: Wij beoordelen dit per situatie
Award Winning E-learning: Ja

Tip! Zorg voor een rustige leeromgeving, tijd en motivatie, audioapparatuur zoals een koptelefoon of luidsprekers voor audio, accountinformatie zoals inloggegevens voor toegang tot het e-learning platform.