What will you in AI-Agents: Automation & Business with LangChain & LLM Apps Course
Build AI agents using frameworks like LangChain, LangFlow, Flowise, LangGraph, Autogen, BabyAGI, and CrewAI.
Leverage LLMs such as GPT‑4, Claude, Gemini, Llama 3, and Mistral with function calling capabilities.
Create RAG-enabled AI agents using vector databases, embeddings, and custom data preparation.
Develop automations for content generation, email campaigns, lead research, and integrating custom tools with APIs.
Learn business-focused skills: pricing AI solutions, marketing strategies, and deploying agents on websites or as standalone tools.
Understand AI security considerations: preventing prompt injections, handling privacy, and copyright compliance.
Program Overview
Module 1: AI Agent Fundamentals
⏳ 30 minutes
Overview of various AI agent frameworks: LangChain, LangFlow, LangGraph, Autogen, BabyAGI, CrewAI.
Introduction to key LLM models (ChatGPT, Claude, Gemini, Llama) and function calling.
Module 2: Tools, Vector DBs & RAG
⏳ 60 minutes
Set up vector databases and embeddings for content retrieval.
Train agents on custom data (PDFs, CSVs) using LlamaIndex, LlamaParse, integrating Flowise/Node tools.
Module 3: Building Agents & Automation
⏳ 75 minutes
Create agents for generating content, emails, and lead generation.
Connect APIs (Python, JavaScript, Make) for task automation and file handling.
Module 4: Flowise & Custom Integration
⏳ 60 minutes
Install and configure Flowise with Node.js environment.
Embed function-calling agents with Gmail, calculator, Serper, Microsoft Copilot, etc.
Module 5: Business Applications & Deployment
⏳ 60 minutes
Learn to deploy agents on websites or as standalone applications.
Develop marketing strategies, set pricing, handle customer acquisition and operations.
Module 6: Security, Compliance & Open-Source LLMs
⏳ 45 minutes
Best practices for guarding against prompt injection and data poisoning.
Use open-source LLMs like Ollama, Llama 3.1 and choose appropriate models for specific tasks.
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Job Outlook
High demand for AI engineers developing task automation and agent-driven solutions—especially in business domains.
Skills supported: LLM integration, prompt engineering, vector search, API connectivity, and toolchain automation.
Salary potential: $110K–$180K+ for developers building AI workflows and RAG-powered applications.
Freelance avenues: Developing and selling custom AI agents for marketing automation, research, customer service, etc.
Explore More Learning Paths
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Specification: AI-Agents: Automation & Business with LangChain & LLM Apps Course
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