Please complete previous Lesson first
📚 Lesson 2.1: Installing Ubuntu/Linux or Using Docker
Module 1: Introduction to AI Systems
• Lesson 1.1: What Are AI Chat Systems? (ChatGPT, DeepSeek, Claude, etc.)
• Lesson 1.2: Components of a Custom AI System (LLM, UI, Database, API)
• Lesson 1.3: Open-Source vs Commercial AI
• Lesson 1.4: Tools We’ll Use in This Course (Overview)
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Module 2: Setting Up Your Environment
• Lesson 2.1: Installing Ubuntu/Linux or Using Docker
• Lesson 2.2: Installing Python and Dependencies
• Lesson 2.3: Overview of Hugging Face Transformers and Open LLMs
• Lesson 2.4: Choosing a Lightweight LLM (e.g., Mistral, LLaMA, DeepSeek LLM)
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Module 3: Running Your Own LLM Locally or on a Server
• Lesson 3.1: Using Ollama to Run LLMs Locally
• Lesson 3.2: Using LM Studio or Text Generation WebUI
• Lesson 3.3: Hosting on a Cloud Server (e.g., Google Colab, RunPod, Vast.ai)
• Lesson 3.4: Loading and Testing Local Models
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Module 4: Creating a Content Management Interface (for Admins)
• Lesson 4.1: Designing the Admin Interface (Streamlit, Gradio, Flask, or React)
• Lesson 4.2: Adding PDFs, CSVs, Text, and URLs to a Vector Database (e.g., ChromaDB, Weaviate, Qdrant)
• Lesson 4.3: Preprocessing and Embedding Your Content (Using SentenceTransformers or OpenAI Embeddings)
• Lesson 4.4: Updating and Managing the Knowledge Base
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Module 5: Building a Chat Interface for Users
• Lesson 5.1: Designing the User Chat Interface (Streamlit, Gradio, or React + Tailwind)
• Lesson 5.2: Connecting UI with Your LLM Backend (via API)
• Lesson 5.3: Implementing Contextual Retrieval with RAG (Retrieval-Augmented Generation)
• Lesson 5.4: Personalizing the Chatbot with System Prompts & Memory
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Module 6: Advanced Features and Customization
• Lesson 6.1: User Authentication and Session Handling
• Lesson 6.2: Saving User Queries and Responses (Using SQLite or Firebase)
• Lesson 6.3: Adding Voice Input and Output (TTS/STT with Coqui.ai, Whisper, etc.)
• Lesson 6.4: Adding Image Upload or Multimodal Features
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Module 7: Deployment and Hosting
• Lesson 7.1: Hosting with Docker
• Lesson 7.2: Using Render, Vercel, or Fly.io for UI Hosting
• Lesson 7.3: Securing Your App (API Keys, HTTPS, Auth)
• Lesson 7.4: Making It Mobile-Friendly (PWA or Android Webview App)
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Module 8: Case Studies and Real-Life Applications
• Lesson 8.1: Educational Bots for Schools
• Lesson 8.2: Customer Support Assistant
• Lesson 8.3: Internal Knowledge Base for Teams
• Lesson 8.4: AI Assistant for Freelancers and Small Businesses
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Module 9: Tools, Plugins, and Deployment
By the end of this module, learners will understand the essential tools, integrations, and deployment methods for running and sharing their AI chat systems—locally or online, securely and reliably.
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Final Project
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