AI Agents Training: Design, Develop, and Deploy

Learn how to create intelligent, autonomous AI agents that can reason, plan, and execute complex tasks using the latest Large Language Models (LLMs) and industry frameworks.

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About Outcomes Modules FAQ

About

This comprehensive training is designed for developers, data scientists, and tech enthusiasts who want to master the creation and deployment of autonomous AI agents. You will move beyond simple prompt engineering to build sophisticated systems that automate workflows and solve real-world problems. You'll gain practical, hands-on experience with leading LLM APIs, agent frameworks (like LangChain or similar), and best practices for creating reliable, ethical, and powerful agents. By the end, you'll be equipped to design, implement, and deploy multi-step AI agents for various domains, including automated research, customer service, and complex data analysis.

What You Will Learn

  • How to design agent architectures (e.g., ReAct, reflection, self-correction).
  • How to integrate Large Language Models (LLMs) with external tools and APIs.
  • How to implement agent memory and manage conversational context over time.
  • How to utilize vector databases for Retrieval Augmented Generation (RAG).
  • How to create and manage multi-agent systems for collaborative tasks.

Skills You Will Gain

LLM Prompt Engineering Agentic Design Patterns Tool & Function Calling Vector Databases & RAG Autonomous System Development Agent Deployment & Monitoring Version Control & Collaboration (Git) Debugging & Observability for Agents

Modules

Module 1: Introduction to AI Agents & Core Concepts 
What an AI Agent is, core components (LLM, Memory, Planning), and key use cases.
Module 2: Agent Architecture & Reasoning 
In-depth look at frameworks (LangChain/LlamaIndex), the ReAct pattern, and decision-making logic.
Module 3: Tool Integration & Data Augmentation (RAG) 
Connecting agents to external data (APIs, web search) and implementing RAG with vector stores.
Module 4: Advanced Agent Patterns & Multi-Agent Systems 
Building multi-step workflows, techniques for self-correction, and creating teams of specialized agents.
Module 5: Deployment, Monitoring, and Ethics 
Containerization (Docker), deployment best practices, security, and designing responsible AI agents.

FAQ

What programming language is required? 
This training focuses primarily on Python, as it is the industry standard for AI and agent development. Prior coding experience in Python is highly recommended.
Do I need prior AI or machine learning experience? 
Basic understanding of programming concepts and familiarity with using LLMs (like ChatGPT) is sufficient. We will cover the AI-specific concepts from a developer's perspective.
What are the main tools we will use? 
We will utilize leading agent frameworks such as LangChain (or equivalent), OpenAI/Google LLMs, and basic cloud platforms for deployment.
Is this course suitable for beginners? 
While the core concepts are introduced clearly, the course moves quickly into advanced development and is best suited for those with an existing coding background.
What will this training help me achieve? 
It will enable you to transition from using LLMs as simple chatbots to building complex, production-ready, autonomous systems that execute multi-step workflows for your business or project.