Published 3/2026
Created by Ardit Sulce • 600,000+ Students Worldwide
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Beginner | Genre: eLearning | Language: English | Duration: 112 Lectures ( 11h 8m ) | Size: 5.4 GB
From beginner to AI engineer -build AI apps, agents, RAG & automations using Python, LangChain, Ollama, Gemini, OpenAI.
What you’ll learn
✓ Build AI Agents from scratch using Python.
✓ Master LangChain 1 to create advanced RAG and Document Context systems.
✓ Implement persistent memory for AI apps using vector and SQL databases.
✓ Automate Google Sheets and spreadsheets with intelligent AI workflows.
✓ Develop multimodal applications for image recognition and voice assistance.
✓ Run private, self-hosted LLMs and local AI agents using Ollama.
✓ Architect AI systems that use web search and external tools to solve tasks.
✓ Build a Claude Code Clone entirely in Python.
Requirements
● Basic Python Knowledge: You should understand variables, loops, functions, and lists.
● No AI Experience Required: We will cover the AI and LLM concepts from the ground up.
Description
Master the most in-demand skill of 2026: Building production-ready AI Agents and Autonomous Apps.
The world is moving beyond simple “chatbots.” Companies today are looking for developers who can build Agents—AI systems that can think, use tools, access databases, and automate complex workflows. This AI Developer Bootcamp is a hands-on, project-based journey designed to take you from a Python coder to an expert AI Engineer.
In this course, we don’t just talk about theory; we build. You will dive deep into LangChain 1.0, mastering Document Context Injection and building full-scale RAG (Retrieval-Augmented Generation) systems. You’ll learn the secrets of AI Memory, giving your agents the ability to remember past interactions using persistent databases.
What Makes This Bootcamp Unique?
We focus on Real-World utility. You will build a suite of powerful projects including
• A Local AI Agent (Claude Code Clone): Build a powerful coding assistant that runs locally.
• Google Sheets Automation: Create AI that can view, edit, and manage private spreadsheets.
• Multimodal Apps: Build a recipe generator that “sees” images and a functional Voice AI Assistant.
• Self-Hostable Models: Learn to build your own LLM service for privacy and cost-efficiency.
By the end of this course, you won’t just know how to prompt an AI—you will know how to architect its brain. Whether you want to automate your own business, land a high-paying AI role, or build the next big AI startup, this bootcamp provides the roadmap, the code, and the confidence to succeed.
What You Will Learn
• AI Agent Architecture: Build agents with web search, memory, and tool-calling capabilities.
• Advanced RAG Systems: Master LangChain 1.0 for high-performance document context injection.
• Automation Mastery: Use Python to bridge LLMs with real-world apps like Google Sheets.
• Local LLM Deployment: Set up self-hostable models for private, secure AI services.
• Multimodal Development: Process images, generate art, and build voice-activated AI tools.
• Structured Outputs: Force LLMs to return reliable, JSON-based data for production apps.
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