AI-Agents: Automation & Business with LangChain & LLM Apps from Udemy

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.

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

Traffic lights

Read about what's good

what should give you pause

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

Reviews summary

Practical ai agent development for business

According to students, this course offers a largely positive and comprehensive journey into AI agents, LLMs, and their business applications. Learners particularly praise its highly practical, hands-on approach, with many useful labs and demonstrations using tools like LangChain, Flowise, and Ollama for open-source LLMs. The instructor's clear and passionate explanations make complex topics accessible. While a few suggest some prior Python knowledge is helpful, the course excels at providing actionable strategies for automation and monetization, consistently updated to remain highly relevant with the latest AI advancements.

The course content is regularly updated to reflect the latest AI advancements.

"I appreciated that the content is regularly updated to reflect the latest in AI, like Llama 3.1 and Groq API."

"Despite the rapid changes in AI, this course has remained relevant and provides current information."

"The instructor is very responsive and clearly keeps the course updated with the latest advancements."

Teaches how to apply AI agents for business automation and monetization.

"This course is a game-changer for automating processes and even generating leads."

"I really appreciated the insights on how to sell AI agents and integrate them into existing businesses."

"It truly delivers on its promise of automation and business applications."

Instructor provides clear, concise, and passionate explanations.

"The instructor explains everything clearly and makes complex topics easy to understand."

"His passion for the subject shines through, making the lessons engaging and informative."

"Instructor is amazing, knows his stuff, and explains it in a very understandable way."

Covers a wide array of AI agent tools and concepts, staying up-to-date.

"This course provides a holistic understanding of AI agents and LLMs from basics to advanced techniques."

"Covers a lot of ground quickly, including Flowise, LangChain, Autogen, and open-source LLMs like Llama."

"I appreciated the coverage of Ollama and Llama 3.1 for local and private AI agent development."

Focuses on real-world use cases and hands-on projects for immediate application.

"The hands-on coding and projects are the strongest part of the course for me, and I appreciate how practical the course is."

"I appreciate the hands-on approach to building AI agents and learning practical solutions for various use cases."

"It’s full of real-world examples and practical advice you can apply immediately."

Benefits from basic Python knowledge; pace may require rewatching for some.

"While the course is great, I think a basic understanding of Python would be beneficial before starting."

"It moves quickly at times, so I sometimes needed to pause and re-watch sections."

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:

Reading list

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AI-Agents

Automation & Business with LangChain & LLM Apps

What's inside

Learning objectives

Syllabus

Traffic lights

Save this course

Reviews summary

Practical ai agent development for business

Activities

Career center

Featured in The Course Notes

Reading list

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