Introduction to Artificial Intelligence

• What is AI? Definition & History
• Types of AI: Narrow AI vs. General AI vs. Super AI
• AI vs. Machine Learning vs. Deep Learning
• Ethical Considerations in AI

AI Applications in the Real World

• AI in Healthcare (Diagnosis & Drug Discovery)
• AI in Business & Marketing (Chatbots, Analytics)
• AI in Finance (Fraud Detection, Algorithmic Trading)
• AI in Transportation (Self-Driving Cars, Traffic Optimization)
• AI in Entertainment (Recommendation Systems, Video Game AI)

Machine Learning Basics

• Supervised, Unsupervised, and Reinforcement Learning
• Common Machine Learning Algorithms
• Data Preprocessing for AI Models
• Overfitting & Underfitting in AI Models

Deep Learning & Neural Networks

• Introduction to Neural Networks
• Understanding Convolutional Neural Networks (CNNs)
• Recurrent Neural Networks (RNNs) & Natural Language Processing (NLP)
• Generative AI & Large Language Models (GPT, DALL·E)

AI Programming & Tools

• Introduction to Python for AI (NumPy, Pandas)
• AI Frameworks: TensorFlow & PyTorch
• Building & Training AI Models
• Deploying AI Models in Real Applications

AI in Automation & Robotics

• AI-Powered Robotics & Autonomous Systems
• AI in Manufacturing & Smart Factories
• AI in Agriculture (Precision Farming & Drones)

AI Ethics & Future Trends

• Bias in AI & Ethical Challenges
• AI & Job Market: Threats & Opportunities
• Future of AI: AGI, Quantum AI, and Beyond