- Level -Advanced
- Prerequisites -Year 1 AI coursework or equivalent experience
- Specializing in advanced AI techniques and real-world applications for industry and research.
- Assessments -Weekly practical assignments, Industry projects, Final thesis
- Module 1: AI for Business and Finance (Weeks 1-2)
Module 1 - AI for Business and Finance (Weeks 1-2)
Learning OutcomeUnderstanding AIs impact on business decision-making.
1.1 AI-powered fraud detection, risk analysis, and financial modeling
1.2 AI-driven business intelligence and customer analytics
1.3 AI in personalized recommendations and behavioral economics
Practical Component
Developing an AI-powered financial risk assessment model
Module 2 - AI in Healthcare and Biomedical Applications (Weeks 3-4)
Learning OutcomeApplying AI to medical diagnosis and treatment.
2.1 AI-powered disease detection and medical image analysis
2.2 AI in personalized medicine and drug discovery
2.3 AI-driven wearable health monitoring systems
Practical Component
Building an AI-powered diagnostic assistant
Module 3 - AI for Smart Cities and Sustainable Development (Weeks 5-6)
Learning OutcomeUnderstanding AIs role in urban planning and sustainability.
3.1 AI-powered traffic management and transportation systems
3.2 AI for energy efficiency and smart grid management
3.3 AI in disaster prediction and environmental monitoring
Practical Component
Developing an AI-driven sustainability model
Module 4 - AI for Security, Cyber Defense, and Ethical AI (Weeks 7-8)
Learning OutcomeExploring AI-driven security and ethical considerations.
4.1 AI-powered cybersecurity and intrusion detection
4.2 AI in digital forensics and fraud prevention
4.3 Ethical AI governance, transparency, and fairness
Practical Component
Implementing an AI-based threat detection system
Module 5 - AI for Emerging Technologies - Metaverse and Quantum AI (Weeks 9-10)
Learning OutcomeExploring the future of AI in immersive and computational technologies.
5.1 AI-driven virtual worlds and digital twin simulations
5.2 AI-powered synthetic humans and deepfake detection
5.3 AI in quantum computing and next-generation AI models
Practical Component
Developing an AI-driven immersive metaverse experience
Module 6 - Industry Collaboration and Research Project (Weeks 11-12)
Learning OutcomeEngaging with real-world AI challenges through research and industry collaboration.
6.1 Working with industry partners on AI projects
6.2 Researching and implementing cutting-edge AI applications
6.3 Presenting AI research findings and project outcomes
Practical Component
Developing and showcasing an industry-ready AI solution