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

AI Agents with Node.js, Python, JavaScript, LangChain, LangGraph, GPT, Cladue & RAG! Automate tasks, sell software

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, n8n, Make, Pydantic 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, Claude, Gemini, Llama, Deepseek & 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, Qwen and Deepseek.

• Installing and Using Ollama with Llama 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-5, 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.