AI Agents & LLMs with RAG: n8n, LangChain, LangGraph, Flowise, MCP & more – with ChatGPT, Gemini, Claude, DeepSeek & Co.

What you'll learn
- Introduction to RAG workflows & tools like Google's NotebookLM with essential tips
- LLM fundamentals & RAG technologies: ChatGPT, Claude, Gemini, Deepseek, Llama, Mistral, xAI, Grok, Function Calling, vector databases, embeddings & chunking
- ChatGPT basics & model management: interface, models, settings, GPTs, OpenAI Playground & test‑time compute
- Building RAG chatbots with Custom GPTs: data preparation from PDFs, HTML webpages, YouTube videos, CSV data sources & writing‑style adaptation
- Open‑source RAG with Ollama & AnythingLLM: installation, models, optimizing chunking & embeddings & creating a local bot
- Agent capabilities & multi‑LLM integration: system prompts, temperature control, web search, scraping & AI‑agent features with Flowise/LangGraph
- OpenAI API & Flowise for RAG agents: pricing, project setup, GDPR compliance, Playground vs. Response API, Node.js installation, Marketplace & OpenAI Assistant
- Advanced Flowise workflows: web scraping, embeddings, vector databases, HTML splitter, JSON import/export & tool agents (email, calendar, Airtable, webhooks)
- Custom chatbot UI & self‑hosting: frontend development, Ollama & LangChain, hosting on Render, Replit branding, WordPress integration & Flowise configuration
- RAG agents with n8n: local installation, interface, triggers/actions, Pinecone automation via Google Drive, workflows & AI‑agent node
- Combining & marketing Flowise & n8n: RAG lead‑bots, website integration, CSS branding, sales, marketing, customer acquisition & offer strategies
- Special RAG strategies: n8n MCPs with Claude Desktop, webhooks, GPT Actions, cache‑augmented generation, GraphRAG, LightRAG & contextual retrieval
- Security, data protection & legal framework: jailbreaks, prompt injections, data poisoning, censorship, GDPR basics, EU AI Act & copyright
- Strategies of leading AI providers & comparison: OpenAI, Anthropic, Microsoft, Google xAI, Meta's LlaMA, Deepseek, Mistral & others

Requirements
- No prior knowledge required—everything is demonstrated step by step.

Description
One of the most important concepts in the AI world is RAG – Retrieval-Augmented Generation!

You need to give LLMs knowledge!

But how do you build powerful RAG chatbots and intelligent AI agents to optimize your business processes and personal projects?

In this course, you'll learn exactly that—comprehensively and clearly explained—using ChatGPT, Claude, Google Gemini, open‑source LLMs, Flowise, n8n, and more!

Fundamentals: LLMs, RAG & Vector DatabasesBuild a solid foundation for your AI projects:

Deepen your knowledge of LLMs: ChatGPT, Claude, Gemini, Deepseek, Llama, Mistral, and many more.

Understand how Function Calling and API communication work in LLMs.

Learn why vector databases and embedding models are the heart of RAG.

Master the ChatGPT interface, GPT models, settings, and the OpenAI Playground.

Explore key concepts like Test‑Time Compute (e.g. OpenAI o1, o3; Deepseek R1).

Discover how Google's NotebookLM works and leverage it effectively for RAG projects.

Simple RAG Implementations with ChatGPT & Custom GPTsGet your first AI applications up and running quickly and easily:

Create your very first RAG bot from PDFs using Custom GPTs.

Turn HTML web pages and YouTube videos into interactive RAG chatbots.

Train ChatGPT on your personal writing style via RAG.

Use CSV data to build smart chatbots and explore the full potential of Custom GPTs.

RAG with Open‑Source LLMs: AnythingLLM & OllamaDive into the world of local AI:

Install and use Ollama: learn about models, commands, and hardware requirements.

Integrate AnythingLLM effectively with Ollama—optimize chunking and embeddings.

Build local RAG chatbots and precisely control language and behavior with system prompts and temperature settings.

Leverage agent capabilities like web search, scraping, and more.

Flowise: RAG with LangChain & LangGraph Made EasyHarness the power of the OpenAI API for professional applications:

Master the OpenAI API, pricing models, GDPR compliance, and project setup.

Build efficient RAG applications via the OpenAI Playground and response APIs.

Install Flowise, manage updates, and become proficient with its interface—including the Marketplace and OpenAI Assistant.

Create comprehensive RAG chatflows with web scraping, embeddings, HTML splitters, and vector databases.

Develop your own chatbot UI and handle Flowise's technical details.

Implement local AI security with Ollama & LangChain and use Flowise's tool‑agent nodes (e.g. email, calendar, Airtable).

Combine Pinecone vector databases with Supabase and Postgres.

Master prompt engineering and sequential agents with human‑in‑the‑loop workflows.

n8n: Building AI Automations & RAG AgentsUse n8n as a powerful automation platform for your AI projects:

Learn local installation, updates, and n8n basics.

Automate Pinecone database updates via Google Drive.

Develop RAG chatbots with AI‑agent nodes, vector databases, and supplementary tools.

Create automated chatbots from websites using HTML requests and scraping.

Hosting, Selling & Monetizing Your RAG AgentsTake your AI projects to market professionally:

Host Flowise and n8n apps on platforms like Render and embed them in websites (HTML, WordPress).

Design branded, professional chatbots and offer them as services or standalone products.

Develop effective marketing and sales strategies for your AI agents.

Advanced Workflows & Specialized RAG TechniquesAdopt professional, cutting‑edge technologies:

Learn advanced techniques like webhooks, MCPs with Claude, GPT Actions, and n8n integration.

Understand the Model Context Protocol (MCP) and build both MCP servers and clients in n8n and Claude Desktop.

Explore innovative RAG strategies such as Cache‑Augmented Generation (CAG), GraphRAG (Microsoft), LightRAG, and Anthropic's Contextual Retrieval.

Optimize chunking, embedding, and Top‑K retrieval for your RAG apps.

Choose the right strategy for your projects and maximize your RAG outcomes.

Security, Privacy & Legal FoundationsProtect your AI projects effectively:

Recognize security risks (Telegram exploits, jailbreaks, prompt injections, data poisoning).

Secure your AI against attacks and respect copyrights in generated content.

Deepen your understanding of GDPR and the upcoming EU AI Act to ensure legal compliance.

Become an expert in AI automations, AI agents & RAG!By the end of this course, you will be fully equipped to build, optimize, and successfully market RAG chatbots, AI agents, and automations.

Who this course is for:
- Private individuals interested in AI and automation who want to build their own RAG agents
- Entrepreneurs looking to become more efficient, save money, or build an AI‑based business
- Anyone eager to learn something new and gain deep insights into RAG agents
- Anyone who wants to finally understand RAG and automate tasks
More Info

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