Complete Agentic AI Bootcamp With LangGraph and Langchain
What you'll learn
- Understand the core principles of Agentic AI and how to design intelligent, autonomous agents for real-world tasks.
- Master building AI agents using LangGraph, including creating workflows, managing agent state, memory, and event-driven behavior.
- Develop and deploy multi-agent collaborative systems that can communicate, reason, and solve complex problems together.
- mplement hands-on projects to create powerful agentic applications like autonomous research agents, task automation systems, and knowledge retrieval assistants.
Requirements
- Basic knowledge of Python programming (variables, functions, classes).
- Understanding of APIs and RESTful services (basic level).
- Familiarity with Large Language Models (LLMs) concepts (like OpenAI, Hugging Face models, etc.).
- Curiosity and willingness to build real-world AI applications — no prior experience with LangGraph needed!
Description
Are you excited about the future of AI where intelligent agents can think, act, and collaborate to solve complex tasks autonomously? Welcome to the Complete Agentic AI Bootcamp with LangGraph and LangChain — your one-stop course to master the art of building agentic AI applications from scratch!
This course is designed to teach you everything you need to know about Agentic AI, LangGraph, and LangChain — two of the most powerful frameworks for building intelligent AI agents and multi-agent systems.
You will start by understanding the fundamentals of Agentic AI — how it differs from traditional AI models, the key components of agents (memory, tools, decision-making), and real-world use cases.
We will then dive deep into LangGraph, a cutting-edge framework that helps you design complex agent workflows using graphs, events, and state transitions. You’ll also learn how to combine LangChain's power with LangGraph to build production-ready agent applications.
Throughout the course, you will build real-world projects step-by-step, including:
Creating single intelligent agents with memory and tool-usage capabilities.
Designing multi-agent collaboration systems with message passing and shared goals.
Implementing autonomous research assistants, task automation bots, and retrieval-augmented generation (RAG) agents.
You will not just learn theory — you will build and deploy multiple end-to-end agentic applications, gaining real-world experience in constructing powerful AI systems.
By the end of this course, you will have the skills and confidence to create your own AI agents and deploy complex agentic applications for various domains like search, research, task planning, customer support, and beyond.
What You Will Learn:
Core concepts behind Agentic AI and how intelligent agents operate.
Hands-on mastery of LangGraph and LangChain for building agent systems.
Building autonomous, event-driven AI workflows with memory, reasoning, and tools.
Deploying and optimizing single-agent and multi-agent applications.
Real-world project experience with RAG agents, auto-research agents, and more.
Why Take This Course?
Hands-on, Project-Based Learning: Build actual AI agent applications, not just toy examples.
Complete and Beginner-Friendly: Designed to take you from beginner to advanced agent builder.
Real-World Skills: Learn techniques that companies are starting to use for next-generation AI products.
Cutting-Edge Technologies: Master the latest innovations in AI agent orchestration with LangGraph and LangChain.
If you are a developer, data scientist, AI/ML engineer, or tech enthusiast looking to future-proof your skills and build cutting-edge AI applications, this is the course for you!
Enroll now and start building the future with intelligent AI agents today!
Who this course is for:
- AI/ML Engineers and Developers who want to build advanced AI agent workflows and autonomous applications.
- Data Scientists and Researchers looking to integrate agentic behavior into their data-driven projects.
- Tech Enthusiasts and Students eager to explore the next generation of AI application development with practical hands-on projects.
- Software Engineers interested in learning how to orchestrate multi-agent systems using modern frameworks like LangGraph.
Instructors
- 4.6 Instructor Rating
- 41,364 Reviews
- 213,413 Students
- 13 Courses
Krish AI Technologies is at the forefront of education in the fields of Data Science, Machine Learning, Generative AI, Deep Learning, and related technologies. Founded by industry veteran Krish Naik, who has over 13 years of experience in the data analytics industry and more than 7 years of teaching expertise, our mission is to equip learners with the skills and knowledge required to excel in the rapidly evolving tech landscape.
Our Expertise: At Krish AI Technologies, we specialize in a comprehensive range of subjects within the realm of artificial intelligence and data science, including:
Data Science: From foundational concepts to advanced techniques, we cover all aspects of data analysis, statistical modeling, and data visualization.
Machine Learning: Our curriculum spans the full spectrum of machine learning algorithms, including supervised and unsupervised learning, clustering techniques, and advanced predictive modeling.
Generative AI: We provide in-depth training on the latest generative AI models and techniques, helping students understand and implement cutting-edge technologies.
Deep Learning: Our courses delve into the mathematical intuition and practical applications of deep learning, covering neural networks, CNNs, RNNs, and more.
Natural Language Processing (NLP): We offer comprehensive training in NLP, including text preprocessing, sentiment analysis, language modeling, and various NLP projects.
- 4.6 Instructor Rating
- 40,890 Reviews
- 210,068 Students
- 10 Courses
I am the Ex Co-founder and Chief AI Engineer of iNeuron and my experience is pioneering in machine learning, deep learning, and computer vision,Generative AI,an educator, and a mentor, with over 15 years' experience in the industry. These are my Udemy Courses where I explain various topics on machine learning, deep learning, and AI with many real-world problem scenarios. I have delivered over 30+ tech talks on data science, machine learning, and AI at various meet-ups, technical institutions, and community-arranged forums. My main aim is to make everyone familiar of ML and AI.