AI-Agents

Automation & Business with LangChain & LLM Apps

Arnold Oberleiter

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.

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:

Python 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:

Pros 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.

Enroll now

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What's inside

Learning objectives

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
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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
Show more
Show less

Syllabus

Introduction and Overview

Welcome

Course Overview

My Goal and a Few Tips

Explanation of the Links

Important Links

Basics: AI Agents, LLMs, Function Calling, Vector Databases & Embeddings

What This Section is About

What are AI-Agents? A quick overview

What are LLMs like ChatGPT, Claude, Gemini, Llama, Mistral etc.

What is Function Calling in LLMs?

Vector Databases, Embedding Models & Retrieval-Augmented Generation (RAG)

AI Agents explained & Tools like Autogen, LangChain, LangGraph, CrewAI & more

What is a API? Function calling for AI-Agents with APIs

Recap: What You Have Learned So Far

Creating Your First AI Agents

What Will You Learn in This Section?

Running Flowise Locally with Node.js: Installing Node

Installing Flowise with Node.js via Command Prompt

The Flowise Interface: LangChain/LangGraph made Easy

Our First AI Agent: Boss, Creative Writer & Title Generator

AI Agent No. 2: Social Media Strategy & Prompt Engineering for AI Agents

AI Agent No. 3: Function Calling, Lead Research on the Web & Personal Emails

Agent 4: Function Calling, Python Interpreter, Calculator & Local Text Storage

Summary: Important Points You Should Not Forget

Advanced AI Agents: RAG, Custom Tools & Actions in Apps

What is This Section About?

RAG AI Agent: Training LLMs on Your Data & Automatic Content Storage

Tips for Better RAG Apps: Firecrawl for Your Web Data

RAG with LlamaIndex & LlamaParse: Data Preparation for PDFs, Docs, CSV & More

LlamaIndex brings easy LlamaParse!

Chunk Size and Chunk Overlap for a Better RAG Application

Overview of Custom Tools in Flowise

Connect any API to Flowise with Custom Tools & JavaScript Functions

Custom Tools and Automation of Gmail with Make (Part. 1)

Automation of Gmail with Make scenarios, Webhooks, & Google API (Part 2)

Recap: What You Have Learned and Mistakes to Avoid

AI Agents for Business: Hosting, Lead Generation & Sales

What Will You Learn Here?

Applications of AI Agents in Business

Example of a Simple AI-Agent then we can sell

External Hosting of Chatbots for Clients (or for us) on Render

Integrating AI Agents in Websites or Using Them as Standalone Apps

Making Standalone Apps More Appealing

Visually Improving Chatbots on Websites: Branding, Style & Integrating Links

Generating Leads, Integrating Audio Models & Additional Functions

Selling AI Agents: Marketing, Customer Acquisition, Offer, Sales & Warranty

Summary: Important Points to Remember!

Creating Your Own AI Assistant, Similar to Microsoft Copilot

What Will We Learn in This Section?

Overview of the Python Code on Github

Installing Visual Studio Code (VS Code) for Python, Javascript & more

Installing Git for Projects from GitHub

Our Project: Microsoft Copilot with Vision as Our Own AI Agent (In Python)

Additional Tips, Use Cases, Different Voices & Prompts

Security, API Costs, Speed & Hardware

Copy my Python Code (if you like)

Code & Requirements for Desktop Recording (Simple)

Recap What You Should Not Forget

AI Agents with Open-Source LLMs: Private & Uncensored AI on Your PC

Pros and Cons of Open-Source LLMs like Llama3.1, Mistral & More

Installing Ollama and Downloading Open-Source LLMs

A Simple Open-Source AI Agent with Llama 3.1 & Ollama (LangChain/LangGraph)

Advanced Open-Source AI Agent with Llama 3.1: Responding to Emails

Local RAG Chatbot with Flowise, Llama3 & Ollama: A Local Langchain App

Insanely fast inference with the Groq API

Llama 3.1: Infos and What Models should you use?

Important Points to Remember

Issues, Security, and Copyrights in AI Agents

What Will We Learn in This Section

Jailbreaks: A Method to Hack LLMs with Prompts

Prompt Injections: Another Security Vulnerability of LLMs

Data Poisoning and Backdoor Attacks

Copyrights & Intellectual Property of Generated Data from AI Agents

Privacy & Protection for your own and Client Data

Recap: Important Points to Remember!

What’s Next?

What’s Next and My Thank You!

Bonus

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Explores industry-standard LLMs like GPT-4, Claude, Gemini, and Llama

Develops foundational knowledge and skills in AI agents and LLMs

Provides hands-on experience in creating, deploying, and integrating AI agents for various applications

Covers advanced techniques for AI agents, including RAG, data preparation, and API integration

Focuses on business applications of AI agents, including lead generation, marketing, and sales

Taught by Arnold Oberleiter, an expert in AI and LLM technology

Teaches Python and JavaScript, essential programming languages for AI agent development

Explores ethical considerations and potential issues in AI agent development, such as security and copyright

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in AI-Agents: Automation & Business with LangChain & LLM Apps with these activities:

Function Calling in LLMs

Show steps

Function calling in LLMs is very useful and versatile. This practice drill is designed to help you develop proficiency with this technique, ensuring your confidence in using it during your AI agent development.

Browse courses on Function Calling

Show steps

Review the documentation on function calling in LLMs.
Implement function calling in your own AI agent code.
Test your AI agent to ensure that the function calling is working correctly.

Show all one activities

Career center

Learners who complete AI-Agents: Automation & Business with LangChain & LLM Apps will develop knowledge and skills that may be useful to these careers: