Ai-Agents: Automation & Business With Langchain & Llm Apps
Published 8/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 10.02 GB | Duration: 9h 28m
AI Agents with Node.js, Python, JavaScript, LangChain, LangGraph, GPT-4o, Llama, and RAG! Automate tasks, sell software
What you'll learn
Basics of AI agents like Autogen, LangChain, LangFlow, Flowise, LangGraph, BabyAGI, CrewAI & more
Basics of LLMs like ChatGPT, Claude, Gemini, Llama, Mistral, GPT-4o & more with Function calling in LLMs
All about vector databases, embedding models & retrieval-augmented generation (RAG)
Creating AI agents for automating content, emails, lead research & more Installation and operation of Flowise with Node
Function calling for external APIs, Python interpreter, calculator, Gmail, Serper, Make & more
RAG AI agent: Training on own data & automatic saving of files on your PC
Data preparation for RAG: PDFs, Docs, CSV & more with LlamaIndex & LlamaParse
Integration and automation of custom tools in Flowise
API connection and automation with JavaScript, Python and Make
AI agents in business: offering, pricing, sales, customer acquisition
Marketing strategies for selling AI agents
Integration of AI agents into websites or as standalone apps
Installation of VS Code and Git
Local Microsoft Copilot with Vision as an AI agent in Python
AI agents with open-source LLMs: Ollama, Llama 3.1 & more
Choosing the right LLM for the AI agent
Issues, security, and copyrights in AI agents
Requirements
No prior knowledge required, everything is shown step by step.
Description
AI agents are on everyone's lips, but few know what they are and even fewer know how to use them.Tools like CrewAI, Autogen, BabyAGI, LangChain, LangGraph, LangFlow etc., sound more complex than they are.Are you ready to master the intricacies of AI agents and leverage their full potential for process automation and selling tailored solutions?Then this course is for you!Dive into "AI Agents: Automation & Business through LangChain Apps"-where you will explore the basic and advanced concepts of AI agents and LLMs, their architectures, and practical applications. Transform your understanding and skills to lead in the AI revolution.This course is perfect for developers, data scientists, AI enthusiasts, and anyone wanting to be at the forefront of AI agent and LLM technology. Whether you want to create AI agents, perfect their automation, or sell tailored solutions, this course provides you with the comprehensive knowledge and practical skills you need.What to expect from this course:Comprehensive knowledge of AI agents and LLMs:Basics of AI Agents and LLMs: Introduction to AI agents like Autogen, LangChain, LangGraph, LangFlow, CrewAI, BabyAGI & their LLMs (GPT-4, Claude, Gemini, Llama & more).Tools and Techniques: Using LangChain, LangGraph, and other tools to create AI agents.Function Calling and Vector Databases: Understanding function calling and using vector databases and embedding models.Creating and deploying AI agents:Installation and Use of Flowise with Node: Step-by-step guides for installing and using Flowise.Creating and Deploying AI Agents for Various Tasks: Developing creative writers, social media strategists, and function-calling agents.Advanced techniques for AI agents:RAG AI Agents: Training LLMs on your own data and automatic local text storage.Data Preparation and Integration: Using LlamaIndex, LlamaParse, and other tools for data preparation and integration in Flowise.API Connection and Automation: Connecting APIs and automating with JavaScript, Python, and Make.AI agents in a business environment:Use Cases and Integration: Hosting and integrating AI agents into websites or as standalone apps.Lead Generation and Marketing: Strategies for generating leads and selling AI agents.Creating your own AI assistant
ython Code and Installation: Developing a local Microsoft Copilot-like AI agent with Vision and Python.Using VS Code and Git: Step-by-step guides for installing and using VS Code and Git.AI agents with open-source LLMsros and Cons of Open-Source LLMs: Using and installing open-source LLMs like Llama 3.Installing and Using Ollama with Llama 3.1 and Other Open-Source LLMs.Creating Open-Source AI Agents: Developing simple and advanced open-source AI agents.Issues, security, and copyrights in AI agents:Security Measures and Privacy: Understanding jailbreaks, prompt injections, and data poisoning.Copyrights and Privacy: Handling copyrights and privacy for generated AI agent data.Practical applications and API integration:API Basics and Integration Skills: Using the OpenAI API, Google API, and more for various applications.Developing AI Apps: Creating apps with Whisper, GPT-4, and more.Innovative tools and agents:Overview of Microsoft Autogen and CrewAI.Implementing Flowise: Integrating Flowise with function calls and open-source LLMs as a chatbot.Harness the power of AI agents and LLM technology to develop solutions and expand your understanding of their applications.At the end of "AI Agents: Automation & Business through LangChain Apps," you will have a holistic understanding of AI agents and LLMs and the skills to use them for various purposes. If you are ready to be at the forefront of this technological revolution, this course is for you.Enroll today and become an expert in AI agents and large language models.
Overview
Section 1: Introduction and Overview
Lecture 1 Welcome
Lecture 2 Explanation of the Links
Lecture 3 Important Links
Section 2: Basics: AI Agents, LLMs, Function Calling, Vector Databases & Embeddings
Lecture 4 What This Section is About
Lecture 5 What are AI-Agents? A quick overview
Lecture 6 What are LLMs like ChatGPT, Claude, Gemini, Llama, Mistral etc.
Lecture 7 What is Function Calling in LLMs?
Lecture 8 Vector Databases, Embedding Models & Retrieval-Augmented Generation (RAG)
Lecture 9 AI Agents explained & Tools like Autogen, LangChain, LangGraph, CrewAI & more
Lecture 10 What is a API? Function calling for AI-Agents with APIs
Lecture 11 Recap: What You Have Learned So Far
Section 3: Creating Your First AI Agents
Lecture 12 What Will You Learn in This Section?
Lecture 13 Running Flowise Locally with Node.js: Installing Node
Lecture 14 Installing Flowise with Node.js via Command Prompt
Lecture 15 The Flowise Interface: LangChain/LangGraph made Easy
Lecture 16 Our First AI Agent: Boss, Creative Writer & Title Generator
Lecture 17 AI Agent No. 2: Social Media Strategy & Prompt Engineering for AI Agents
Lecture 18 AI Agent No. 3: Function Calling, Lead Research on the Web & Personal Emails
Lecture 19 Agent 4: Function Calling, Python Interpreter, Calculator & Local Text Storage
Lecture 20 Summary: Important Points You Should Not Forget
Section 4: Advanced AI Agents: RAG, Custom Tools & Actions in Apps
Lecture 21 What is This Section About?
Lecture 22 RAG AI Agent: Training LLMs on Your Data & Automatic Content Storage
Lecture 23 Tips for Better RAG Apps: Firecrawl for Your Web Data
Lecture 24 RAG with LlamaIndex & LlamaParse: Data Preparation for PDFs, Docs, CSV & More
Lecture 25 Chunk Size and Chunk Overlap for a Better RAG Application
Lecture 26 Overview of Custom Tools in Flowise
Lecture 27 Connect any API to Flowise with Custom Tools & JavaScript Functions
Lecture 28 Custom Tools and Automation of Gmail with Make (Part. 1)
Lecture 29 Automation of Gmail with Make scenarios, Webhooks, & Google API (Part 2)
Lecture 30 Recap: What You Have Learned and Mistakes to Avoid
Section 5: AI Agents for Business: Hosting, Lead Generation & Sales
Lecture 31 What Will You Learn Here?
Lecture 32 Applications of AI Agents in Business
Lecture 33 Example of a Simple AI-Agent then we can sell
Lecture 34 External Hosting of Chatbots for Clients (or for us) on Render
Lecture 35 Integrating AI Agents in Websites or Using Them as Standalone Apps
Lecture 36 Making Standalone Apps More Appealing
Lecture 37 Visually Improving Chatbots on Websites: Branding, Style & Integrating Links
Lecture 38 Generating Leads, Integrating Audio Models & Additional Functions
Lecture 39 Selling AI Agents: Marketing, Customer Acquisition, Offer, Sales & Warranty
Lecture 40 Summary: Important Points to Remember!
Section 6: Creating Your Own AI Assistant, Similar to Microsoft Copilot
Lecture 41 What Will We Learn in This Section?
Lecture 42 Overview of the Python Code on Github
Lecture 43 Installing Visual Studio Code (VS Code) for Python, Javascript & more
Lecture 44 Installing Git for Projects from GitHub
Lecture 45 Our Project: Microsoft Copilot with Vision as Our Own AI Agent (In Python)
Lecture 46 Additional Tips, Use Cases, Different Voices & Prompts
Lecture 47 Security, API Costs, Speed & Hardware
Lecture 48 Copy my Python Code (if you like)
Lecture 49 Code & Requirements for Desktop Recording (Simple)
Lecture 50 Recap What You Should Not Forget
Section 7: AI Agents with Open-Source LLMs: Private & Uncensored AI on Your PC
Lecture 51 What is This Section About?
Lecture 52 Pros and Cons of Open-Source LLMs like Llama3.1, Mistral & More
Lecture 53 Installing Ollama and Downloading Open-Source LLMs
Lecture 54 A Simple Open-Source AI Agent with Llama 3.1 & Ollama (LangChain/LangGraph)
Lecture 55 Advanced Open-Source AI Agent with Llama 3.1: Responding to Emails
Lecture 56 Local RAG Chatbot with Flowise, Llama3 & Ollama: A Local Langchain App
Lecture 57 Insanely fast inference with the Groq API
Lecture 58 Llama 3.1: Infos and What Models should you use?
Lecture 59 Important Points to Remember
Section 8: Issues, Security, and Copyrights in AI Agents
Lecture 60 What Will We Learn in This Section
Lecture 61 Jailbreaks: A Method to Hack LLMs with Prompts
Lecture 62 Prompt Injections: Another Security Vulnerability of LLMs
Lecture 63 Data Poisoning and Backdoor Attacks
Lecture 64 Copyrights & Intellectual Property of Generated Data from AI Agents
Lecture 65 Privacy & Protection for your own and Client Data
Lecture 66 Recap: Important Points to Remember!
Section 9: What's Next?
Lecture 67 What's Next and My Thank You!
Lecture 68 Bonus
To everyone who wants to learn something new and gain deep insights into AI agents,To entrepreneurs who want to become more efficient, save money, or build an AI business,To individuals interested in AI and wanting to build their own agents,To anyone who wants to automate tasks
What you'll learn
Basics of AI agents like Autogen, LangChain, LangFlow, Flowise, LangGraph, BabyAGI, CrewAI & more
Basics of LLMs like ChatGPT, Claude, Gemini, Llama, Mistral, GPT-4o & more with Function calling in LLMs
All about vector databases, embedding models & retrieval-augmented generation (RAG)
Creating AI agents for automating content, emails, lead research & more Installation and operation of Flowise with Node
Function calling for external APIs, Python interpreter, calculator, Gmail, Serper, Make & more
RAG AI agent: Training on own data & automatic saving of files on your PC
Data preparation for RAG: PDFs, Docs, CSV & more with LlamaIndex & LlamaParse
Integration and automation of custom tools in Flowise
API connection and automation with JavaScript, Python and Make
AI agents in business: offering, pricing, sales, customer acquisition
Marketing strategies for selling AI agents
Integration of AI agents into websites or as standalone apps
Installation of VS Code and Git
Local Microsoft Copilot with Vision as an AI agent in Python
AI agents with open-source LLMs: Ollama, Llama 3.1 & more
Choosing the right LLM for the AI agent
Issues, security, and copyrights in AI agents
Requirements
No prior knowledge required, everything is shown step by step.
Description
AI agents are on everyone's lips, but few know what they are and even fewer know how to use them.Tools like CrewAI, Autogen, BabyAGI, LangChain, LangGraph, LangFlow etc., sound more complex than they are.Are you ready to master the intricacies of AI agents and leverage their full potential for process automation and selling tailored solutions?Then this course is for you!Dive into "AI Agents: Automation & Business through LangChain Apps"-where you will explore the basic and advanced concepts of AI agents and LLMs, their architectures, and practical applications. Transform your understanding and skills to lead in the AI revolution.This course is perfect for developers, data scientists, AI enthusiasts, and anyone wanting to be at the forefront of AI agent and LLM technology. Whether you want to create AI agents, perfect their automation, or sell tailored solutions, this course provides you with the comprehensive knowledge and practical skills you need.What to expect from this course:Comprehensive knowledge of AI agents and LLMs:Basics of AI Agents and LLMs: Introduction to AI agents like Autogen, LangChain, LangGraph, LangFlow, CrewAI, BabyAGI & their LLMs (GPT-4, Claude, Gemini, Llama & more).Tools and Techniques: Using LangChain, LangGraph, and other tools to create AI agents.Function Calling and Vector Databases: Understanding function calling and using vector databases and embedding models.Creating and deploying AI agents:Installation and Use of Flowise with Node: Step-by-step guides for installing and using Flowise.Creating and Deploying AI Agents for Various Tasks: Developing creative writers, social media strategists, and function-calling agents.Advanced techniques for AI agents:RAG AI Agents: Training LLMs on your own data and automatic local text storage.Data Preparation and Integration: Using LlamaIndex, LlamaParse, and other tools for data preparation and integration in Flowise.API Connection and Automation: Connecting APIs and automating with JavaScript, Python, and Make.AI agents in a business environment:Use Cases and Integration: Hosting and integrating AI agents into websites or as standalone apps.Lead Generation and Marketing: Strategies for generating leads and selling AI agents.Creating your own AI assistant
ython Code and Installation: Developing a local Microsoft Copilot-like AI agent with Vision and Python.Using VS Code and Git: Step-by-step guides for installing and using VS Code and Git.AI agents with open-source LLMsros and Cons of Open-Source LLMs: Using and installing open-source LLMs like Llama 3.Installing and Using Ollama with Llama 3.1 and Other Open-Source LLMs.Creating Open-Source AI Agents: Developing simple and advanced open-source AI agents.Issues, security, and copyrights in AI agents:Security Measures and Privacy: Understanding jailbreaks, prompt injections, and data poisoning.Copyrights and Privacy: Handling copyrights and privacy for generated AI agent data.Practical applications and API integration:API Basics and Integration Skills: Using the OpenAI API, Google API, and more for various applications.Developing AI Apps: Creating apps with Whisper, GPT-4, and more.Innovative tools and agents:Overview of Microsoft Autogen and CrewAI.Implementing Flowise: Integrating Flowise with function calls and open-source LLMs as a chatbot.Harness the power of AI agents and LLM technology to develop solutions and expand your understanding of their applications.At the end of "AI Agents: Automation & Business through LangChain Apps," you will have a holistic understanding of AI agents and LLMs and the skills to use them for various purposes. If you are ready to be at the forefront of this technological revolution, this course is for you.Enroll today and become an expert in AI agents and large language models. Overview
Section 1: Introduction and Overview
Lecture 1 Welcome
Lecture 2 Explanation of the Links
Lecture 3 Important Links
Section 2: Basics: AI Agents, LLMs, Function Calling, Vector Databases & Embeddings
Lecture 4 What This Section is About
Lecture 5 What are AI-Agents? A quick overview
Lecture 6 What are LLMs like ChatGPT, Claude, Gemini, Llama, Mistral etc.
Lecture 7 What is Function Calling in LLMs?
Lecture 8 Vector Databases, Embedding Models & Retrieval-Augmented Generation (RAG)
Lecture 9 AI Agents explained & Tools like Autogen, LangChain, LangGraph, CrewAI & more
Lecture 10 What is a API? Function calling for AI-Agents with APIs
Lecture 11 Recap: What You Have Learned So Far
Section 3: Creating Your First AI Agents
Lecture 12 What Will You Learn in This Section?
Lecture 13 Running Flowise Locally with Node.js: Installing Node
Lecture 14 Installing Flowise with Node.js via Command Prompt
Lecture 15 The Flowise Interface: LangChain/LangGraph made Easy
Lecture 16 Our First AI Agent: Boss, Creative Writer & Title Generator
Lecture 17 AI Agent No. 2: Social Media Strategy & Prompt Engineering for AI Agents
Lecture 18 AI Agent No. 3: Function Calling, Lead Research on the Web & Personal Emails
Lecture 19 Agent 4: Function Calling, Python Interpreter, Calculator & Local Text Storage
Lecture 20 Summary: Important Points You Should Not Forget
Section 4: Advanced AI Agents: RAG, Custom Tools & Actions in Apps
Lecture 21 What is This Section About?
Lecture 22 RAG AI Agent: Training LLMs on Your Data & Automatic Content Storage
Lecture 23 Tips for Better RAG Apps: Firecrawl for Your Web Data
Lecture 24 RAG with LlamaIndex & LlamaParse: Data Preparation for PDFs, Docs, CSV & More
Lecture 25 Chunk Size and Chunk Overlap for a Better RAG Application
Lecture 26 Overview of Custom Tools in Flowise
Lecture 27 Connect any API to Flowise with Custom Tools & JavaScript Functions
Lecture 28 Custom Tools and Automation of Gmail with Make (Part. 1)
Lecture 29 Automation of Gmail with Make scenarios, Webhooks, & Google API (Part 2)
Lecture 30 Recap: What You Have Learned and Mistakes to Avoid
Section 5: AI Agents for Business: Hosting, Lead Generation & Sales
Lecture 31 What Will You Learn Here?
Lecture 32 Applications of AI Agents in Business
Lecture 33 Example of a Simple AI-Agent then we can sell
Lecture 34 External Hosting of Chatbots for Clients (or for us) on Render
Lecture 35 Integrating AI Agents in Websites or Using Them as Standalone Apps
Lecture 36 Making Standalone Apps More Appealing
Lecture 37 Visually Improving Chatbots on Websites: Branding, Style & Integrating Links
Lecture 38 Generating Leads, Integrating Audio Models & Additional Functions
Lecture 39 Selling AI Agents: Marketing, Customer Acquisition, Offer, Sales & Warranty
Lecture 40 Summary: Important Points to Remember!
Section 6: Creating Your Own AI Assistant, Similar to Microsoft Copilot
Lecture 41 What Will We Learn in This Section?
Lecture 42 Overview of the Python Code on Github
Lecture 43 Installing Visual Studio Code (VS Code) for Python, Javascript & more
Lecture 44 Installing Git for Projects from GitHub
Lecture 45 Our Project: Microsoft Copilot with Vision as Our Own AI Agent (In Python)
Lecture 46 Additional Tips, Use Cases, Different Voices & Prompts
Lecture 47 Security, API Costs, Speed & Hardware
Lecture 48 Copy my Python Code (if you like)
Lecture 49 Code & Requirements for Desktop Recording (Simple)
Lecture 50 Recap What You Should Not Forget
Section 7: AI Agents with Open-Source LLMs: Private & Uncensored AI on Your PC
Lecture 51 What is This Section About?
Lecture 52 Pros and Cons of Open-Source LLMs like Llama3.1, Mistral & More
Lecture 53 Installing Ollama and Downloading Open-Source LLMs
Lecture 54 A Simple Open-Source AI Agent with Llama 3.1 & Ollama (LangChain/LangGraph)
Lecture 55 Advanced Open-Source AI Agent with Llama 3.1: Responding to Emails
Lecture 56 Local RAG Chatbot with Flowise, Llama3 & Ollama: A Local Langchain App
Lecture 57 Insanely fast inference with the Groq API
Lecture 58 Llama 3.1: Infos and What Models should you use?
Lecture 59 Important Points to Remember
Section 8: Issues, Security, and Copyrights in AI Agents
Lecture 60 What Will We Learn in This Section
Lecture 61 Jailbreaks: A Method to Hack LLMs with Prompts
Lecture 62 Prompt Injections: Another Security Vulnerability of LLMs
Lecture 63 Data Poisoning and Backdoor Attacks
Lecture 64 Copyrights & Intellectual Property of Generated Data from AI Agents
Lecture 65 Privacy & Protection for your own and Client Data
Lecture 66 Recap: Important Points to Remember!
Section 9: What's Next?
Lecture 67 What's Next and My Thank You!
Lecture 68 Bonus
To everyone who wants to learn something new and gain deep insights into AI agents,To entrepreneurs who want to become more efficient, save money, or build an AI business,To individuals interested in AI and wanting to build their own agents,To anyone who wants to automate tasks
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