Ai-Agents: Automation & Business With Langchain & Llm Apps

AI Agents with Node.js, Python, JavaScript, LangChain, LangGraph, GPT-4o, Llama, and RAG! Automate tasks, sell software

[b]What you'll learn[/b]

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

[b]Requirements[/b]

No prior knowledge required, everything is shown step by step.

[b]Description[/b]

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 Tongue

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 LLMs Tongue

ros 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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