Course description
What will i learn?
- Basics of AI agents like Autogen, LangChain, LangFlow, Flowise, LangGraph, BabyAGI, CrewAI & more
- All about vector databases, embedding models & retrieval-augmented generation (RAG)
- Function calling for external APIs, Python interpreter, calculator, Gmail, Serper, Make & more
- Data preparation for RAG: PDFs, Docs, CSV & more with LlamaIndex & LlamaParse
- API connection and automation with JavaScript, Python and Make
- Basics of LLMs like ChatGPT, Claude, Gemini, Llama, Mistral, GPT-4o & more with Function calling in LLMs
- Creating AI agents for automating content, emails, lead research & more Installation and operation of Flowise with Node
- RAG AI agent: Training on own data & automatic saving of files on your PC
- Integration and automation of custom tools in Flowise
- AI agents in business: offering, pricing, sales, customer acquisition
- Integration of AI agents into websites or as standalone apps
- Local Microsoft Copilot with Vision as an AI agent in Python
- Choosing the right LLM for the AI agent
- Marketing strategies for selling AI agents
- Installation of VS Code and Git
- AI agents with open-source LLMs: Ollama, Llama 3.1 & more
- Issues, security, and copyrights in AI agents
Requirements
- No prior knowledge required, everything is shown step by step.
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What This Section is About
00:05:15
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What are AI-Agents A quick overview
00:05:11
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What are LLMs like ChatGPT, Claude, Gemini, Llama, Mistral etc
00:30:06
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What is Function Calling in LLMs
00:09:45
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Vector Databases, Embedding Models & Retrieval-Augmented Generation (RAG)
00:10:00
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AI Agents explained & Tools like Autogen, LangChain, LangGraph, CrewAI & more
00:28:45
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What is a API Function calling for AI-Agents with APIs
00:04:45
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Recap What You Have Learned So Far
00:08:45
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Problems with the Installation of Flowise in Node.js Fix it!
00:03:30
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The Flowise Interface LangChainLangGraph made Easy
00:19:42
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Our First AI Agent Boss, Creative Writer & Title Generator
00:15:00
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AI Agent No. 2 Social Media Strategy & Prompt Engineering for AI Agents
00:19:45
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AI Agent No. 3 Function Calling, Lead Research on the Web & Personal Emails
00:24:45
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Agent 4 Function Calling, Python Interpreter, Calculator & Local Text Storage
00:18:42
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Summary Important Points You Should Not Forget
00:09:45
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What Will You Learn in This Section
00:03:45
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Running Flowise Locally with Node.js Installing Node
00:05:00
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Installing Flowise with Node.js via Command Prompt
00:04:30
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What is This Section About
00:03:30
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RAG AI Agent Training LLMs on Your Data & Automatic Content Storage
00:29:45
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ips for Better RAG Apps Firecrawl for Your Web Data
00:04:45
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RAG with LlamaIndex & LlamaParse Data Preparation for PDFs, Docs, CSV & More
00:14:30
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LlamaIndex brings easy LlamaParse!
00:03:00
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Chunk Size and Chunk Overlap for a Better RAG Application
00:09:30
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Overview of Custom Tools in Flowise
00:05:15
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Connect any API to Flowise with Custom Tools & JavaScript Functions
00:19:45
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Custom Tools and Automation of Gmail with Make (Part. 1)
00:09:45
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Automation of Gmail with Make scenarios, Webhooks, & Google API (Part 2)
00:14:45
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Recap What You Have Learned and Mistakes to Avoid
00:14:30
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What Will You Learn Here
00:02:03
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Applications of AI Agents in Business
00:04:30
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Example of a Simple AI-Agent then we can sell
00:18:47
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External Hosting of Chatbots for Clients (or for us) on Render
00:23:45
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Integrating AI Agents in Websites or Using Them as Standalone Apps
00:13:45
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Making Standalone Apps More Appealing
00:12:30
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Visually Improving Chatbots on Websites Branding, Style & Integrating Links
00:27:42
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Generating Leads, Integrating Audio Models & Additional Functions
00:18:45
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Selling AI Agents Marketing, Customer Acquisition, Offer, Sales & Warranty
00:34:45
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Summary Important Points to Remember!
00:04:49
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What Will We Learn in This Section
00:04:45
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Overview of the Python Code on Github
00:09:00
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Installing Visual Studio Code (VS Code) for Python, Javascript & more
00:05:00
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Installing Git for Projects from GitHub
00:02:00
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Our Project Microsoft Copilot with Vision as Our Own AI Agent (In Python)
00:34:30
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Additional Tips, Use Cases, Different Voices & Prompts
00:14:31
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Security, API Costs, Speed & Hardware
00:09:00
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Copy my Python Code (if you like)
00:02:45
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Recap What You Should Not Forget
00:07:48
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What is This Section About
00:03:00
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Pros and Cons of Open-Source LLMs like Llama3.1, Mistral & More
00:05:02
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Installing Ollama and Downloading Open-Source LLMs
00:14:45
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A Simple Open-Source AI Agent with Llama 3.1 & Ollama (LangChainLangGraph)
00:09:30
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Advanced Open-Source AI Agent with Llama 3.1 Responding to Emails
00:19:15
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Local RAG Chatbot with Flowise, Llama3 & Ollama A Local Langchain App
00:15:15
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Insanely fast inference with the Groq API
00:09:45
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Llama 3.1 Infos and What Models should you use
00:04:00
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Important Points to Remember
00:08:15
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What Will We Learn in This Section
00:04:15
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Jailbreaks A Method to Hack LLMs with Prompts
00:09:45
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Prompt Injections Another Security Vulnerability of LLMs
00:10:00
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Data Poisoning and Backdoor Attacks
00:05:00
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Copyrights & Intellectual Property of Generated Data from AI Agents
00:09:45
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Privacy & Protection for your own and Client Data
00:09:45
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Recap Important Points to Remember!
00:08:43
