đ Course Overview
AI Agent Development (60h) āĻšāϞ⧠āĻāĻāĻāĻŋ Advanced, Practical & Project-Based Course, āϝā§āĻāĻžāύ⧠intelligent AI Agents design, build, test āĻāĻŦāĻ deploy āĻāϰāĻžāϰ professional skills āĻļā§āĻāĻžāύ⧠āĻšāĻŦā§āĨ¤
āĻāĻ course-āĻ Python, OpenAI APIs, LangChain, LangGraph, CrewAI, AutoGen, MCP, Vector Databases āĻāĻŦāĻ RAG-āĻāϰ practical use āĻļā§āĻāĻžāύ⧠āĻšāĻŦā§āĨ¤
Real-World Business Use Cases, Multi-Agent Systems āĻ End-to-End Projects-āĻāϰ āĻŽāĻžāϧā§āϝāĻŽā§ learners AI-powered automation, research, customer support āĻāĻŦāĻ business workflows-āĻāϰ āĻāύā§āϝ production-ready AI Agents āϤā§āϰāĻŋ āĻāϰāĻžāϰ skills āĻ āϰā§āĻāύ āĻāϰāĻŦā§āĨ¤
Basic Python & AI Fundamentals Recommended.
đ Course Information
- Course Name: AI Agent Development
- Duration: 60 Hours
- Level: Intermediate to Advanced
- Language: Bangla + English
- Class Type: Online / Offline
- Prerequisite: Basic Python Programming & AI Fundamentals
- Hands-on Practice: Yes
- Real-world Projects: Yes
- Certificate: Yes
đ¯ What You’ll Learn
āĻāĻ āĻā§āϰā§āϏ⧠āĻāĻĒāύāĻŋ āĻļāĻŋāĻāĻŦā§āύâ
â Introduction to AI Agents
â Large Language Models (LLMs)
â AI Agent Architecture
â Prompt Engineering for Agents
â OpenAI API Integration
â LangChain Fundamentals
â LangGraph Workflows
â CrewAI Multi-Agent Systems
â Microsoft AutoGen Basics
â MCP (Model Context Protocol)
â RAG (Retrieval-Augmented Generation)
â Vector Databases (ChromaDB / FAISS)
â Memory Management
â Tool Calling & Function Calling
â API Integration
â Web Scraping for AI Agents
â AI Workflow Automation
â Agent Security & Best Practices
â Deployment & Monitoring
â End-to-End AI Agent Projects
đ Course Modules
Module 1 â Introduction to AI Agents
- What is an AI Agent?
- AI Agent vs Chatbot
- Types of AI Agents
- Real-world Applications
Module 2 â Foundations of LLMs
- Large Language Models
- Tokenization
- Prompt Engineering
- Context Windows
- Function Calling
Module 3 â Building AI Agents
- LangChain Fundamentals
- Agent Memory
- Agent Tools
- Agent Planning
- Task Execution
Module 4 â Multi-Agent Systems
- CrewAI
- LangGraph
- Microsoft AutoGen
- Agent Collaboration
- Workflow Orchestration
Module 5 â Knowledge & Retrieval
- RAG Architecture
- Vector Databases
- Embeddings
- ChromaDB
- FAISS
- Document Retrieval
Module 6 â APIs & Integrations
- OpenAI API
- Google Gemini API
- Third-party APIs
- Webhooks
- REST API Integration
- External Tool Integration
Module 7 â Deployment & Security
- Agent Deployment
- Cloud Deployment Basics
- Monitoring
- Logging
- AI Security
- Responsible AI
Module 8 â Capstone Projects
- AI Customer Support Agent
- AI Research Assistant
- AI Sales Assistant
- AI Content Generation Agent
- AI Business Automation Agent
- Multi-Agent Workflow Project
- Final Industry-Level Capstone Project
đ¨âđģ Who Should Join?
āĻāĻ āĻā§āϰā§āϏāĻāĻŋ āĻŦāĻŋāĻļā§āώāĻāĻžāĻŦā§ āĻāĻĒāϝā§āĻā§â
- Python Developers
- AI Engineers
- Machine Learning Engineers
- Software Developers
- Data Scientists
- Automation Engineers
- Technical Freelancers
- Startup Founders
- IT Professionals
- Anyone who wants to build AI Agents professionally
đ After Completing This Course
āĻāĻ āĻā§āϰā§āϏ āĻļā§āώ āĻāϰāĻžāϰ āĻĒāϰ āĻāĻĒāύāĻŋ āĻĒāĻžāϰāĻŦā§āύâ
- Professional AI Agents Design āĻ Develop āĻāϰāϤā§āĨ¤
- LangChain, LangGraph, CrewAI āĻāĻŦāĻ AutoGen āĻŦā§āϝāĻŦāĻšāĻžāϰ āĻāϰ⧠Intelligent Agent āϤā§āϰāĻŋ āĻāϰāϤā§āĨ¤
- RAG āĻ Vector Database āĻŦā§āϝāĻŦāĻšāĻžāϰ āĻāϰ⧠Knowledge-based AI Systems āϤā§āϰāĻŋ āĻāϰāϤā§āĨ¤
- APIs, External Tools āĻāĻŦāĻ Databases-āĻāϰ āϏāĻžāĻĨā§ AI Agents Connect āĻāϰāϤā§āĨ¤
- Business Automation, Customer Support āĻāĻŦāĻ Research-āĻāϰ āĻāύā§āϝ AI Agent Solutions āϤā§āϰāĻŋ āĻāϰāϤā§āĨ¤
- Multi-Agent Collaboration System Develop āĻāϰāϤā§āĨ¤
- AI Agents Deploy, Monitor āĻāĻŦāĻ Maintain āĻāϰāϤā§āĨ¤
- Enterprise-level AI Automation Projects-āĻ āĻāĻžāĻ āĻāϰāĻžāϰ āĻŽāϤ⧠Industry-ready Skills āĻ āϰā§āĻāύ āĻāϰāϤā§āĨ¤
đŧ Practical Projects
- AI Customer Support Agent
- AI Research Assistant
- AI Sales & Lead Generation Agent
- AI Content Creation Agent
- AI Email Automation Agent
- AI Business Operations Assistant
- RAG-based Document Q&A System
- Multi-Agent Workflow Automation
- AI Personal Productivity Assistant
- Final Enterprise AI Agent Capstone Project