Master of Science in Artificial Intelligence – 2024 – 17th Intake University of Moratuwa

Master of Science in Artificial Intelligence – 2024 – 17th Intake University of Moratuwa| The University of Moratuwa’s Faculty of Information Technology, through its Department of Computational Mathematics, has announced the commencement of the 17th intake for the Master of Science (M.Sc.) and Postgraduate Diploma (PG Diploma) in Artificial Intelligence for the year 2024. This program is designed to equip students with the knowledge and skills necessary to harness modern Artificial Intelligence (AI) technologies, paving the way for innovative solutions and diverse career opportunities in the rapidly evolving tech landscape.

Entry Requirements

To be eligible for admission, applicants must meet one of the following criteria:

1. Hold an Honours degree in Information Technology or Information Technology and Management from the University of Moratuwa, Sri Lanka.
2. Possess an Honours degree in Engineering from the University of Moratuwa, Sri Lanka, with a relevant specialization approved by the Senate.
3. Have a four-year degree from a recognized university in fields such as Information Technology, Computer Science, or Engineering, or another relevant area approved by the Senate.
4. A three-year degree from a recognized university in a relevant field, combined with a minimum of two years of appropriate experience, as approved by the Senate.
5. Membership in a recognized professional institute, with relevant experience and academic background, as approved by the Senate.

Course Structure

The M.Sc. program spans two years on a part-time basis, while the PG Diploma is a one-year part-time program. Both programs are conducted online, with lectures, assignments, and seminars typically held on weekends. Students who complete the first year successfully can opt for a Postgraduate Diploma in Artificial Intelligence. The M.Sc. program includes a one-year research project in the second year.

Courses covered in the program include:

• Essentials of AI
• Deep Learning
• Evolutionary Computing
• Artificial Cognitive Systems
• Fuzzy Reasoning
• Natural Language Processing
• Computer Vision
• Cloud Computing for AI
• Reinforcement Learning
• Generative AI
• Semantic Web and Ontological Engineering
• Applied Machine Learning
• Data Mining & Data Warehousing
• Distributed Computing Concepts for AI
• Deductive Reasoning & Logic Programming
• Embedded Robotics