Core Subjects

1. Machine Learning (Supervised, Unsupervised, and Reinforcement Learning)

2. Deep Learning (Neural Networks, CNNs, RNNs, GANs, Transformers)

3. Artificial Intelligence Fundamentals

4. Data Structures & Algorithms for AI

5. Mathematical Foundations for AI (Linear Algebra, Probability, Statistics)

6. Optimization Techniques

7. Natural Language Processing (NLP)

8. Computer Vision & Image Processing

9. Big Data & AI

10. AI Ethics & Fairness

11. Robotics & Autonomous Systems

12. AI in Cloud Computing

Advanced & Elective Subjects

1. Reinforcement Learning & Decision Making

2. Probabilistic Graphical Models

3. Explainable AI (XAI)

4. Human-Computer Interaction in AI

5. Edge AI & AI on IoT Devices

6. Bioinformatics & AI

7. AI for Finance & Business Intelligence

8. AI in Cybersecurity

9. Generative AI & Large Language Models (LLMs)

10. Self-Supervised & Few-Shot Learning

11. Quantum Computing & AI

12. Neuroscience & Cognitive Computing

Practical & Research-Based Courses

1. AI Capstone Project / Thesis

2. AI Software Development & Deployment

3. AI for Healthcare & Medical Imaging

4. AI-driven Automation & Robotics

5. Entrepreneurship in AI & Startups

6. AI for Climate Science & Sustainability