The Master of Science in Artificial Intelligence (MSc AI) is an advanced postgraduate program designed to develop expertise in artificial intelligence, machine learning, and intelligent systems. The program typically covers advanced programming, mathematical foundations, machine learning, deep learning, computer vision, natural language processing, big data analytics, generative AI, and AI ethics. It combines theoretical study with practical projects and research to prepare graduates for advanced technical and research-oriented careers in AI
Duration
Discipline
Level
Affiliation
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Must have a Bachelor's Degree in the related field.
Trimester 1: Programming & Mathematical Foundations
Subjects |
Introduction to Data Science |
Advanced Mathematical Methods for AI |
Programming for AI |
Trimester 2: Core AI & Machine Learning
Subjects |
Machine Learning |
Concepts of Artificial Intelligence |
Pattern Recognition |
Theory of Optimisation |
Trimester 3: Deep Learning & Big Data
Subjects |
Deep Learning and Neural Networks |
Big Data Analytics |
Natural Language Processing |
Intelligent Interaction |
Trimester 4: Advanced Intelligence Systems
Subjects |
Computer Vision |
Generative AI |
Responsible AI |
Trimester 5: Emerging Technologies & Management
Subjects |
Metaverse |
Managing AI Applications |
Research Methodology (AI-focused) |
Tech Entrepreneurship |
Trimester 6: Research, Entrepreneurship & Capstone
Subjects |
AI Society |
Master's Applied Capstone (Research + Product) |
After completing the program, graduates will be able to:
Apply advanced concepts of artificial intelligence and machine learning to complex problems.
Design, develop, train, and evaluate intelligent systems and AI models.
Apply advanced machine learning and deep learning techniques to real-world applications.
Analyze and process large datasets using appropriate data science and analytics methods.
Develop AI applications involving computer vision and natural language processing.
Apply generative AI, large language models, and other emerging AI technologies.
Use mathematical, statistical, and computational methods for AI research and development.
Evaluate the performance, reliability, fairness, security, and ethical implications of AI systems.
Conduct independent research and develop innovative AI-based solutions.
Design and implement substantial AI projects or research theses.
Demonstrate advanced analytical, problem-solving, communication, and technical skills.
