Core Modules:

1. Introduction to Artificial Intelligence

   • History and applications of AI
   • Key concepts and terminologies

2. Machine Learning Fundamentals

   • Supervised, unsupervised, and reinforcement learning
   • Algorithms like linear regression, decision trees, and clustering

3. Deep Learning

   • Neural networks
   • Convolutional Neural Networks (CNNs)
   • Recurrent Neural Networks (RNNs)

4. Natural Language Processing (NLP)

   • Text analysis and sentiment analysis
   • Chatbot development
   • Transformers and large language models

5. Computer Vision

   • Image recognition
   • Object detection
   • Face recognition

Specialized Modules:

1. AI Ethics and Governance

   • Bias in AI
   • Ethical considerations in AI applications

2. AI in Real-World Applications

   • AI in healthcare, finance, and other industries
   • Case studies and projects

3. Reinforcement Learning

   • Q-learning
   • Policy gradients

4. Generative AI