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Build Ai Agents & Agentic 2026: Python, Langchain, Langgraph - charlie - 12-01-2026
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![[Obrazek: _ef61ec02d54e96bc88d74a4f73f7c2cb.png]](https://i126.fastpic.org/big/2026/0112/cb/_ef61ec02d54e96bc88d74a4f73f7c2cb.png)
Build Ai Agents & Agentic 2026: Python, Langchain, Langgraph
Published 1/2026
Created by MetaTact AI Experts
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All | Genre: eLearning | Language: English | Duration: 31 Lectures ( 2h 10m ) | Size: 1.4 GB [/center]
Build intelligent agents with LangChain, ChromaDB, Streamlit. Then use LangGraph to transform them into agentic systems
What you'll learn
Build intelligent AI agents from scratch using Python, Ollama, LangChain & LangGraph-no API costs, runs locally with complete privacy control
Master agentic patterns: ReAct reasoning, chain-of-thought prompting & self-correction loops to create agents that think and decide autonomously
Implement web search, file analysis & persistent memory using ChromaDB vector database-build agents that remember conversations across sessions
Create production-ready AI applications with Streamlit UI, autonomous decision-making & multi-step workflows-portfolio projects included
Requirements
Basic Python knowledge
Windows PC
Stable Internet Connection
Description
What you'll learnBuild a complete AI agent from scratch using 100% open-source tools with no API costsUnderstand the fundamental differences between simple chatbots and intelligent agentic AI systemsImplement web search capabilities so your agent can access real-time information from the internetCreate persistent memory systems using ChromaDB vector database for conversation historyAdd file upload functionality to analyze PDFs and text documents with AIMaster the ReAct pattern (Reasoning + Acting) for intelligent decision-makingImplement chain-of-thought prompting for complex problem-solvingBuild self-correction loops where agents validate and improve their own responsesDesign agentic workflows using LangGraph with state machines and conditional routingRun large language models locally using Ollama (llama3.2) with complete privacyCreate interactive chat interfaces with Streamlit for production-ready applicationsImplement semantic search and vector embeddings for intelligent memory retrievalBuild autonomous agents that choose tools, plan actions, and execute tasks independentlyCustomize agent personality and behavior through advanced prompt engineeringCourse DescriptionStop paying for expensive AI APIs. Start building your own intelligent agents.This comprehensive course teaches you how to build agentic AI systems from the ground up using modern open-source technologies. Unlike simple chatbots, agentic AI can reason, plan, use tools, remember conversations, and make autonomous decisions-all running locally on your machine with zero API costs.What Makes This Course Different?- 100% Open Source - No proprietary APIs, no vendor lock-in, no recurring costs - Complete Source Code Included - Every lecture comes with fully working code you can download and customize - Hands-On Practice Exercises - Carefully designed exercises that enhance your skills and add powerful features to your agent Production-Ready Skills - Build real applications, not toy examples. - Local Development - Everything runs on your laptop with full data privacy- Modern AI Stack - Learn the tools used by professional AI engineers todayWhat You'll BuildBy the end of this course, you'll have created a fully functional agentic AI application with these capabilities:- Web Search Integration - Agent searches DuckDuckGo for current information automatically - Document Analysis - Upload PDFs or text files and ask questions about their content - Persistent Memory - Conversations are remembered across sessions using vector database technology - Intelligent Decision Making - Agent decides when to search, when to analyze files, or when to use existing knowledge - Self-Correction - Validates its own answers and refines them if needed - Autonomous Planning - Uses the ReAct pattern to reason before taking action - State Management - Built with LangGraph for complex multi-step workflows - User Sessions - Multiple users can have separate conversations with persistent history - Customizable Personality - Change agent behavior through prompt engineeringTechnologies You'll MasterAI & Machine Learning:Ollama (Local LLM Runtime)LangChain (Agent Framework)LangGraph (State Machine Workflows)llama3.2 (Open Source Language Model)Vector Databases & Memory:ChromaDB (Vector Database)Embeddings and Semantic SearchSentence TransformersWeb Development:Streamlit (UI Framework)Python (Programming Language)API Integration (OpenLibrary, DuckDuckGo)Agent Patterns:ReAct (Reasoning + Acting)Chain-of-Thought PromptingSelf-Correction LoopsAutonomous Decision MakingWho This Course Is For- Python developers who want to build AI applications without expensive APIs - Data scientists looking to add AI agent development to their skillset - Software engineers interested in practical AI implementation - Tech entrepreneurs building AI-powered products - Students learning modern AI development techniques - Professionals wanting to understand how intelligent agents work - Anyone interested in building privacy-focused AI applications- No prior AI experience required - we start from fundamentals and build up to advanced concepts step by step.PrerequisitesBasic Python programming knowledge (variables, functions, loops)Familiarity with command line/terminalA computer with at least 8GB recommended for better performance)Willingness to learn and experimentWhat Makes This Course UniquePractice Exercises Included - Each major section includes hands-on exercises designed to deepen your understanding and add real functionality to your agent. Solutions are provided so you can verify your work.Complete Source Code - Download working code for every single lecture. No guessing, no incomplete examples-just production-ready code you can run immediately.Regular Updates - As AI technology evolves, this course will be updated with new techniques and tools.From Theory to Practice - We don't just explain concepts-we build real, working applications you can deploy and customize.Modern Best Practices - Learn the patterns and techniques used by professional AI engineers in 2024 and beyond.Course OutcomesBy completing this course, you will:Understand how modern AI agents work under the hood Build production-ready agentic AI applications Implement advanced AI patterns like ReAct and Chain-of-Thought Master vector databases and semantic search Create agents that can search the web, analyze files, and remember conversations Design autonomous systems that make intelligent decisions Save hundreds of dollars in API costs by running AI locally Have portfolio projects to showcase your AI development skillsJoin Thousands of Students Building the Future of AIEnroll now and start building intelligent AI agents today. With our 30-day money-back guarantee, you have nothing to lose and everything to gain.Stop using AI. Start building it.
Who this course is for
Anyone who wants to learn to create an AI Agent
Anyone who wants to improve their AI Agent creation skills
Anyone who wants to learn LangGraph and LangChain
Anyone who wants to learn to instruct an AI Agent
Anyone who wants to use open-source tools to build AI Agents
Cytat:https://rapidgator.net/file/abc3bb51f6d0464af2539b0433e85ce0/Build_AI_Agents_&_Agentic_2026_Python_LangChain_LangGraph.part2.rar.html
https://rapidgator.net/file/339b84853b9509e40bc740e5ca622486/Build_AI_Agents_&_Agentic_2026_Python_LangChain_LangGraph.part1.rar.html
https://frdl.io/fjvyteyd4t68/Build_AI_Agents_%2526_Agentic_2026_Python_LangChain_LangGraph.part2.rar.html
https://frdl.io/f890p9tuphj5/Build_AI_Agents_%2526_Agentic_2026_Python_LangChain_LangGraph.part1.rar.html