Python + AI + Agentic AI Combo
Course Duration: 10–12 Weeks (Flexible) | Mode: Offline/Online
Goal: To build students’ skills from Python basics to practical AI and modern Agentic AI systems. Students will learn to code, train simple AI models, and create intelligent AI agents that can automate real tasks. By the end, they will be able to build functional AI-powered solutions for projects, learning, or career readiness.
MODULE 1: Programming with Python (Week 1–3)
Python Basics
- Variables, Data Types
- Operators & Expressions
- Conditional Statements
- Loops
- Functions & Modules
Intermediate Python
- Lists, Tuples, Dictionaries, Sets
- File Handling
- Error Handling
- OOP Basics (Classes, Objects, Inheritance, Encapsulation)
Python for AI
- NumPy basics
- Pandas basics
- Matplotlib intro
MODULE 2: AI & Machine Learning Foundations (Week 4–6)
AI Fundamentals
- What is AI?
- Types of AI (Narrow, General)
- Real-world AI apps
Machine Learning Basics
- Supervised, Unsupervised learning
- Classification & Regression concepts
- Model training workflow
- Evaluation metrics (accuracy, confusion matrix)
Practical ML (Beginner Friendly)
- Using Scikit-Learn
- Linear Regression
- Decision Trees
- K-means Clustering
MODULE 3: Generative AI Basics (Week 7)
Understanding GenAI
- What are generative models?
- LLMs (GPT, Llama, Claude) overview
- Text, image, audio generation
- Prompt engineering basics:
- Roles
- Few-shot
- Structured prompts
- Chain-of-thought
MODULE 4: Introduction to Agentic AI (Week 8)
- What is an AI Agent?
- Agents vs Traditional AI models
- Core components of agents:
- Planning
- Memory
- Tools
- Actions
- Types of AI Agents (Task agents, research agents, chat agents, automation agents)
MODULE 5: Building AI Agents (Week 9–10)
Agent Architecture Basics
- Tool calling
- Function calling in LLMs
- Agent workflows:
- Sense → Plan → Act → Reflect
- Sense → Plan → Act → Reflect
No-Code Agent Builders
- ChatGPT Assistants
- Google AI Studio
- Langflow
- Flowise
Python-Based Agents
- Using LangChain basics
- Using OpenAI API / local LLMs
- Building custom tools (functions)
- Agent memory systems
MODULE 6: Agent Automation & Integrations (Week 11)
- Integrating agents with APIs
- Using Zapier / Make for workflow automation
- Connecting agents to databases
- Connecting agents to the web (browsing, scraping basics)
- Multi-agent systems (concept-level)
MODULE 7: Practical & Interview Preparation (Week 12)
- Practical
- Interview Preparation