Module 1: Introduction to AI

• What is Artificial Intelligence?
• History and evolution of AI
• Importance of AI in modern world
• Overview of Computer Science
• Applications of AI in daily life

Module 2: Basics of AI Concepts

• Types of AI (Narrow AI, General AI)
• AI vs Human Intelligence
• Introduction to algorithms
• Basics of data and information

Module 3: Machine Learning Basics

• Introduction to Machine Learning
• Types of Machine Learning:
• Supervised Learning
• Unsupervised Learning
• Real-life examples of ML
• Basic model concepts

Module 4: Data Handling & Processing

• Types of Data (Structured & Unstructured)
• Data Collection Methods
• Data Cleaning & Preparation
• Introduction to data analysis

Module 5: Natural Language Processing (NLP)

• Introduction to Natural Language Processing
• Text and speech recognition
• Chatbots and virtual assistants
• Language translation basics

Module 6: Computer Vision

• Introduction to Computer Vision
• Image recognition basics
• Face detection concepts
• Applications in security and healthcare

Module 7: AI Tools & Applications

• Overview of AI tools (basic platforms)
• AI in mobile apps and websites
• Introduction to automation tools
• Everyday AI applications

Module 8: Ethics & Impact of AI

• Ethical use of AI
• Bias and fairness in AI
• Impact of AI on jobs and society
• Responsible AI usage

Module 9: Practical & Mini Projects

• Simple AI-based projects (no coding / basic coding)
• Chatbot creation (basic)
• Data classification example
• Hands-on activities

Module 10: Assessment & Certification

• Quiz and assignments
• Project evaluation
• Final assessment/test