Agentic AI with Python

Agentic AI Course Overview:

Agentic AI Course is designed to train technical freshers and software developers to build AI-powered, autonomous agents using Python and modern AI frameworks. The program focuses on enabling learners to design, develop, and deploy AI agents within real-world software systems.
Students will gain hands-on experience in integrating Large Language Models (LLMs), designing agent workflows, and embedding AI agents into web applications to meet current and future industry demands.

Course Structure

• book_2 Module 1: Python Programming for AI Applications
  • • Python syntax and programming fundamentals
  • • Variables, data types, and control structures
  • • Functions and modular programming
  • • Data structures: lists, tuples, dictionaries, sets
  • • File handling and exception management
  • • Writing clean and maintainable Python code
• book_2 Module 2: Python with Object-Oriented Programming
  • • Object-Oriented Programming concepts
  • • Classes, abstract classes, interfaces
  • • Types of inheritance
  • • Method Resolution Order (MRO)
  • • Introduction to Streamlit
  • • Build basic GUI applications using Streamlit
• book_2 Module 3: Python with SQLite Database
  • • Introduction to SQLite
  • • Understanding serverless databases
  • • CRUD operations using Python + SQLite
  • • Database relationships
  • • Build small standalone applications
• book_2 Module 4: Introduction to FastAPI
  • • REST API fundamentals
  • • HTTP methods: GET, POST, PUT
  • • Build APIs using FastAPI & SQLite
  • • Integrate APIs with JavaScript frontend
  • • Build Agentic bot for CRUD operations
• book_2 Module 5: Prompt Engineering for Developers
  • • Principles of effective prompt design
  • • System, user, and assistant prompts
  • • Dynamic prompt creation using Python
  • • Structured outputs (JSON-based responses)
  • • Prompt optimization and error handling
• book_2 Module 6: Agentic AI & LLM Fundamentals
  • • Introduction to AI and Generative AI
  • • Understanding Large Language Models (LLMs)
  • • Interacting with LLMs using Python
  • • Setup Ollama and run local LLMs
  • • Build custom chatbot applications
• book_2 Module 7: Building AI Agents Using Python
  • • Designing task-oriented AI agents
  • • Tool calling and function execution
  • • API and database integration
  • • Context and memory management
  • • Custom agent logic development
  • • Model Context Protocol [MCP] tools configuration
  • • Create a simple client-server using MCP tools
  • • Create custom tools using MCP + OPENAI LLM hands-on.
• book_2 Module 8: RAG (Retrieval Augmented Generation)
  • • RAG architecture basics
  • • FAISS vector database
  • • Sentence transformers & query-based agents
  • • Knowledge base creation
  • • Build apps like PDF reader bot, DB bot
• book_2 Module 9: Advanced RAG & Agent Frameworks
  • • FAISS, LangChain, OpenAI integration
  • • Build agents using LangChain
  • • Build agents using Google Antigravity
  • • Build agents using Microsoft Autogen
  • • Convert APIs using FastAPI
  • • Connect frontend with live APIs
  • • Projects: AI PDF Chat, GitHub Chat, File Search AI
• book_2 Module 10: Multiple Agents Orchestration
  • • Learning Multiple Agent concecpt
  • • What is Crew AI , LangGraph
  • • Create multiple agents for database automation using OpenAI & Gemini
  • • Multiple Agent decision making, chaining and nesting concept
• book_2 Module 11: Cost Optimization & Efficiency
  • • Token optimization
  • • Response caching
  • • Model selection strategies
  • • Streaming responses
  • • Cost monitoring & budgeting
• book_2 Module 12: Production Deployment
  • • Deploy projects using GitHub
  • • Deploy FastAPI applications
  • • Host AI agents
  • • Connect live APIs to frontend
  • • Build real-world deployable AI systems

Real Client AI Projects

Students work on real AI automation requirements received from our software clients, building enterprise-grade AI agents that solve practical business problems. Projects include Natural Language Report Generation, where multiple AI agents collaborate to convert user requests into optimized database queries, and Intelligent CRM Automation, where AI agents identify leads, trigger targeted campaigns, and generate personalized responses for lead conversion. View Project Workflows →

Certification as Trainee Agentic AI Developer:

Upon successful completion of the course, students receive the "Trainee Agentic AI Developer" certification, jointly awarded by EJOBINDIA and OS4ED India Pvt. Ltd., our software development division.