Ai Workflows & Agents: Langchain, Langgraph, Gemini, Openai
Published 10/2025
Created by Rakesh Kumar,Mukesh Mankotia
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Intermediate | Genre: eLearning | Language: English | Duration: 26 Lectures ( 4h 13m) | Size: 1.71 GB
Hands-on guide to mastering AI development -build real AI agents and integrate modern LLMs like ChatGPT, Gemini & Ollama
What you'll learn
100% practical approach - less theory, more coding. Continuously expanding content to reflect the latest tools, frameworks, and best practices
Empower learners to build intelligent AI agents using modern tools like LangChain, LangGraph, Gemini, and OpenAI-through practical workflows.
Simplify complex LLM workflows into modular, hands-on Python examples and projects.
Help learners automate tasks and design real-world AI solutions with confidence
Requirements
Basic understanding of Python (variables, functions, and packages)
Familiarity with using the command line or terminal & a computer with internet access (Windows, macOS, or Linux)
This course is designed to guide you step-by-step with practical code samples and continuous updates.
Curiosity to explore AI tools and build real-world projects No prior experience with LangChain, Gemini, OpenAI, or LLMs is required
Description
Are you ready to go beyond theory and actually build AI applications that work? then you at the right place here. Hi, I'm Rakesh Kumar - a software architect and educator with 15+ years of experience building enterprise applications and intelligent systems.[Co-instructor: Mukesh Mankotia who assisted from backend in this content creation]This course is designed for developers who want to become AI builders, not just prompt writers. You'll learn how to develop, configure, and deploy real-world AI systems using Python, JupyterLab, and modern SDKs like Ollama, OpenAI, Gemini, LangChain, and LangGraphThroughout all practical videos, you'll gain hands-on experience creating, debugging, and connecting multiple AI frameworks.From installing Ollama locally to integrating Gemini's APIs, from building dynamic LangChain graphs to developing your own AI Agent, everything is covered step-by-step with live coding in Python.By the end of this course, you will be able to:Set up and run local LLMs using OllamaConnect and interact with ChatGPT (OpenAI) and Gemini (Google) APIsCreate intelligent workflows with LangChain and LangGraphDesign conditional logic, multi-node agents, and autonomous AI systemsUse Python and JupyterLab for clean, efficient, and modular AI development100% practical approach - less theory, more codingIncludes real projects with LangChain and LangGraphStep-by-step configuration guides for SDKs and APIsWhether you're an experienced Python developer or a beginner looking to transition into AI, this course gives you everything you need to start building production-ready AI systems today.
Who this course is for
Python developers eager to build real-world AI workflows and intelligent agents
Educators and content creators looking to teach or demo LLMs using reproducible, modular code
AI enthusiasts and students curious about LangChain, Gemini, OpenAI, and LangGraph
Tech professionals seeking to automate tasks, integrate APIs, and explore frontier models hands-on
Code:
Bitte
Anmelden
oder
Registrieren
um Code Inhalt zu sehen!
