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Artificial Intelligence

Developing Agentic AI Systems (with LangChain)

Group Training
Course Outline

Overview

Developing Agentic AI Systems (with LangChain) will help you stay on the cutting edge of AI. This course is an intensive four-day workshop designed for developers already proficient with LLM systems who are ready to take their skills to the next level. Participants will transcend conventional LLM applications, learning to architect, build, and deploy sophisticated autonomous agents. Along the way, they’ll gain mastery over the intricate architectures of intelligent agents, navigate the dynamic ecosystem of specialized tools, using advanced techniques to build secure, robust, and effective agentic systems. Emerge equipped to engineer the next generation of intelligent solutions, commanding newfound capabilities to address complex challenges with unprecedented autonomy. Participants will also master the architecture of intelligent agent teams, leverage specialized frameworks, and utilize effective communication protocols.

On Day 4, students will take a deep dive into LangChain, exploring its core components and learning how to construct and test applications effectively. LangChain is the leading open source software framework that helps facilitate the integration of large language models (LLMs) into agentic AI applications.

Duration

4 Days

Who Should Take This Course

Audience

Developers, Data Scientists, Data Engineers, Machine Learning Engineers, MLOps professionals, DevOps professionals.

Prerequisites

Participants should have solid skills in Python, basic experience with machine learning, and solid understanding of LLMs and LLM systems.

Why You Should Take This Course

Developing Agentic AI Systems (with LangChain) ensures participants are able to:

  • Understand the architecture of LLM agents and their core components Navigate the ecosystem of
    libraries, utilities, and models for agentic AI Acquire hands-on experience building and evaluating
    LLM agents
  • Develop practical knowledge to build and test agentic systems for maximum robustness Learn how to
    optimize agent prompts and sampling parameters for greater performance Build the skills and
    understanding to develop agentic LLM solutions
  • Understand the fundamental principles and mechanisms of multi-agent AI, including various
    frameworks, architectures, and inter-agent communication protocols.
  • Gain experience designing and implementing specialized AI agents, and orchestrating their
    collaboration within multi-agent systems to tackle complex tasks.
  • Become familiar with the parallels between multi-agent AI and common engineering concepts, such as
    asynchronous programming and zero-trust.

Course Outline

Developing Agentic AI Systems (with LangChain)

Day 1: Foundations for Agentic Systems

  1. Introduction to Agentic AI
  2. Agentic AI Ecosystem
  3. LLM Tools and Structured Output
  4. Agent Memory, Observation and Planning

Day 2: Practical Design of Agentic Systems

  1. Communication Protocols for Agents
  2. Agentic Prompting Strategies
  3. Safety Mechanisms for Agents
  4. Testing and Diagnostics for Agents

Day 3: Designing Multi-Agent Systems

  1. Overview of Multi-Agent AI
  2. Frameworks for Building Multi-Agent Systems
  3. Multi-Agent Architectures and Communications
  4. Agent Specialization

Day 4: LangChain

  1. LangChain Fundamentals
  2. LangChain Components
  3. Building Applications with LangChain
  4. Testing Applications with LangChain
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