Generative AI & Agentic AI Course
The Generative AI & Agentic AI course is designed to help students, graduates, software professionals, and job seekers learn how to build AI-powered applications, intelligent chatbots, automation systems, and autonomous AI agents.
This course combines Generative Artificial Intelligence (GenAI), Large Language Models (LLMs), Python programming, prompt engineering, RAG applications, and AI agent development with practical projects.
It is suitable for students who want to start a career in Artificial Intelligence, Machine Learning, AI Development, or Intelligent Automation.
1. Course Syllabus – Generative AI & Agentic AI
Here is a suggested industry-oriented syllabus that can be used for a software training institute such as MIIT Computer Education.
Introduction to Artificial Intelligence
Introduction to AI, Machine Learning and Deep Learning
Generative AI vs Traditional AI
Applications of AI in business and industry
Introduction to Large Language Models (LLMs)
Understanding ChatGPT, Gemini and Claude
Python Programming for AI
Python fundamentals
Variables, data types and operators
Conditional statements and loops
Functions, lists, tuples, sets and dictionaries
Object-oriented programming
File handling and exception handling
NumPy and Pandas basics
Working with APIs and JSON
Generative AI Fundamentals
How Generative AI works
Neural networks and Transformers
LLM architecture basics
Tokens, context windows and embeddings
Text, image and code generation
Introduction to open-source AI models
Prompt Engineering
Introduction to prompt engineering
Zero-shot and few-shot prompting
Role-based prompting
Chain-of-thought concepts and reasoning prompts
Structured output and JSON prompting
Prompt templates
Prompt optimization and testing
LLM Application Development
Working with LLM APIs
OpenAI API integration
Chat completion and streaming
Conversation history and memory
Structured responses
Error handling and API management
Building AI applications using Python
LangChain Framework
Introduction to LangChain
Models, prompts and chains
Document loaders
Text splitters
Embeddings
Vector databases
Retrieval systems
Building LLM-powered applications
Retrieval-Augmented Generation (RAG)
Introduction to RAG
RAG architecture
Document processing and chunking
Embedding generation
Vector search and similarity search
ChromaDB, FAISS or other vector stores
Retrieval and answer generation
Advanced RAG concepts
Source-based answers and hallucination reduction
Introduction to Agentic AI
What is Agentic AI?
Generative AI vs Agentic AI
AI agents and autonomous systems
Agent architecture
Planning and reasoning
Tool calling and function calling
Agent memory and context
Decision-making and task execution
AI Agent Development
Building AI agents using Python
LangChain agents
LangGraph fundamentals
Agent state management
Conditional workflows
Tool integration
Human-in-the-loop workflows
Agent error handling
Multi-agent systems
Advanced AI Agent Technologies
CrewAI fundamentals
Multi-agent collaboration
Agent orchestration
Model Context Protocol (MCP)
MCP servers and clients
Connecting agents to external tools
AI workflow automation using n8n
Agentic RAG
AI Application Deployment
Building APIs using FastAPI
Streamlit application development
Git and GitHub
Docker fundamentals
AI application deployment
Cloud deployment basics
AI application monitoring
Security, evaluation and guardrails
This syllabus combines core GenAI application development with the newer agent-development concepts used in industry-oriented programs.
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Course Duration
Course Level | Duration |
|---|---|
Generative AI Fundamentals | 4 Weeks |
Generative AI Developer | 8 Weeks |
Agentic AI Development | 4 Weeks |
Projects & Deployment | 2 Weeks |
Total Course Duration | 3–4 Months |
The duration is a suggested training structure for an institute. Actual duration can vary depending on students’ programming knowledge and class timings.
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Eligibility
Students pursuing B.Tech, B.Sc, B.Com, BCA, MCA, or other degree programs.
Fresh graduates looking to enter the IT industry.
Working professionals interested in AI development.
Python developers who want to specialize in Generative AI.
Beginners who are willing to learn Python programming.
Recommended prerequisite: Basic computer knowledge. Students without Python knowledge should begin with Python fundamentals before progressing to advanced AI development.
Career Opportunities
After completing the course, learners can explore the following career paths:
Job Role | Main Skills |
|---|---|
Generative AI Developer | Python, LLMs, Prompt Engineering |
AI Application Developer | Python, APIs, FastAPI |
AI Agent Developer | LangGraph, Tool Calling, Agent Workflows |
LLM Application Engineer | RAG, Embeddings, Vector Databases |
AI Automation Developer | AI Agents, n8n, MCP |
Junior AI Engineer | Python, AI Applications, Deployment |
These are potential career paths, not guaranteed placement outcomes.
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Course Description for MIIT Computer Education Website
Generative AI & Agentic AI Training Course in Hayathnagar
Master Generative AI, Build Intelligent AI Agents & Automate Real-World Tasks
MIIT Computer Education & Spoken English offers a practical Generative AI & Agentic AI training program designed for students, graduates, and working professionals who want to develop future-ready AI skills.
Learn Python programming, Generative AI fundamentals, Large Language Models (LLMs), Prompt Engineering, LangChain, Retrieval-Augmented Generation (RAG), and AI Agent Development.
Our training program focuses on hands-on learning, real-time projects, and practical implementation of AI technologies. Students will learn to build intelligent chatbots, AI-powered applications, document assistants, autonomous AI agents, and business automation solutions.
What You Will Learn
Generative AI and Large Language Models
Python Programming for AI
Prompt Engineering
ChatGPT API Integration
LangChain and LangGraph
Retrieval-Augmented Generation (RAG)
Vector Databases and Embeddings
AI Agent Development
Multi-Agent Systems
Model Context Protocol (MCP)
AI Workflow Automation using n8n
AI Application Development and Deployment
Why Choose MIIT Computer Education?
Practical, hands-on training
Industry-oriented course curriculum
Real-time project development
Beginner-friendly learning approach
Classroom and practical lab sessions
Career-oriented technical training
Start your journey into Generative AI and Agentic AI with MIIT Computer Education, Hayathnagar.
Frequently Asked Questions
Q1. What is Generative AI?
Generative AI is a technology that creates new content such as text, images, code, audio, and videos using trained AI models.
Q2. What is Agentic AI?
Agentic AI refers to AI systems that can plan tasks, use tools, interact with external systems, and execute multi-step workflows with varying degrees of autonomy.
Q3. Is Python required for Generative AI?
Python is strongly recommended for AI application development. Beginners can learn Python as part of the course.
Q4. What is the difference between Generative AI and Agentic AI?
Generative AI focuses on generating content. Agentic AI focuses on accomplishing tasks by using AI models, tools, and workflows.
Q5. Can freshers learn this course?
Yes. Freshers can learn the course by starting with Python fundamentals and gradually progressing to Generative AI and AI Agent Development.
Q6. What is the course duration?
A comprehensive Generative AI & Agentic AI training program can be structured over approximately 3–4 months, depending on the syllabus and practical project requirements.
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