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