• views: 91
• date: 5 August 2025
• posted by: voska89

What you'll learn
AI & LLM Foundations
LangChain Core Skills
Building with Streamlit
Building a Scalable Chatbot
Testing and Observability (with LangSmith)
Requirements
Basic Python Knowledge (Required)
Familiarity with the Command Line (Helpful)
Curiosity About Chatbots and Generative AI
Description
Build Real-World AI Chatbots with Python, LangChain & StreamlitFrom Zero to Production-Ready Conversational AI using LLMs, LangGraph, LangSmith & StreamlitAre you ready to build powerful, intelligent chatbots using cutting-edge AI tools?In this hands-on masterclass, you'll learn how to design, build real-world AI chatbots using Python, LangChain, Streamlit, and modern LLM platforms like OpenAI and Ollama. Whether you're a developer, data scientist, or AI enthusiast—this course will teach you everything you need to create production-ready AI assistants from scratch.You'll go far beyond the basics. By the end, you'll have built a full-stack chatbot with memory, LLM switching, persistent conversation history and LangSmith-powered observability and debugging.What You'll BuildA memory-enabled chatbot with a modern Streamlit UIMulti-provider LLM support (OpenAI & Ollama)Persistent chat history using SQLiteFully traceable workflows using LangSmithA ready-to-deploy conversational assistant for your business or clientsKey Technologies CoveredPython – Core scripting for AI ChatbotLangChain – Prompting, chains, memory, parsingStreamlit – Frontend chat UI and user interactionLangSmith – Debugging, tracing, observabilityOpenAI & Ollama – Cloud and local LLM integrationSQLChatMessageHistory – Long-term memory via SQLitePrompt engineering – System + human messages and history placeholdersWhat You Will LearnHow to design a modular and scalable LLM chatbotHow to build Streamlit chat UIsHow to use LangChain's memory components and prompt templatesHow to switch between OpenAI and Ollama models on the flyHow to structure LangChain chains using RunnableLambda and RunnableWithMessageHistoryHow to trace, debug, and compare model outputs using LangSmithHow to store and retrieve chat history from a SQL databaseHow to deploy your chatbot locally or to the cloudWho This Course Is ForPython developers exploring Generative AI and LLMsFull-stack or backend developers integrating chatbots into appsQA & automation engineers building smart validation toolsData scientists wanting to build LLM-based assistantsIndie hackers and startup founders creating AI-powered toolsStudents and career switchers entering the AI engineering spacePrerequisitesBasic knowledge of Python (functions, loops, data structures)Familiarity with running Python scripts and installing packagesNo prior LangChain or LLM experience required – everything is explained from scratch!By the end of this course, you'll have the skills and confidence to build intelligent, scalable AI chatbots that feel truly interactive—and production-grade.
SDETs, QA & Automation Engineers,Python Developers,AI & ML Enthusiasts
Homepage








   
   
   

Forex Trading

Crypto Trading. 20 USD Bonus after KYC

We need your support!
Make a donation to help us stay online
        
Bitcoin (BTC)
bc1q08g9d22cxkawsjlf8etuek2pc9n2a3hs4cdrld
	
Bitcoin Cash (BCH)
qqvwexzhvgauxq2apgc4j0ewvcak6hh6lsnzmvtkem

Ethereum (ETH)
0xb55513D2c91A6e3c497621644ec99e206CDaf239

Litecoin (LTC)
ltc1qt6g2trfv9tjs4qj68sqc4uf0ukvc9jpnsyt59u

USDT (ERC20)
0xb55513D2c91A6e3c497621644ec99e206CDaf239

USDT (TRC20)
TYdPNrz7v1P9riWBWZ317oBgJueheGjATm

0 1 2 3 4 5

| Print version |

	Information
		Users of GUESTS are not allowed to comment this publication.