The Master of Science (Artificial Intelligence) program provides students with a specialization in the field of artificial intelligence. This is achieved through the completion of academic coursework in key areas and research projects. This program aims to produce graduates in the field of artificial intelligence who are knowledgeable, creative and innovative in designing interesting and effective learning, as required by the country, especially in dealing with students from the new generation who are born as critical human beings.

The program can be completed within 1 year and 6 month – 3 years for full-time candidates and 2 – 5 years for part-time candidates.  Candidates who enroll in this program are required to register for the following courses:

Master by Research 

Research Methodology Courses

• GRU50204 (Audit)

– Machine Learning: Researching algorithms and techniques that enable machines to learn and improve from data without being explicitly programmed.

– Natural Language Processing: Studying how to enable computers to understand, interpret, and generate human language, including speech recognition, machine translation, sentiment analysis, and text generation.

– Computer Vision: Exploring methods to enable machines to understand and interpret visual information, such as object recognition, image and video analysis, and scene understanding.

– Robotics: Researching techniques for designing and programming robots to perceive their environment, make decisions, and carry out physical tasks autonomously.

– Knowledge Representation and Reasoning: Investigating methods for representing and organizing knowledge in a form that can be used by AI systems to reason, make decisions, and solve complex problems.

– Multi-Agent Systems: Studying how multiple AI agents can interact, collaborate, and coordinate with each other to achieve specific goals, such as in applications like autonomous vehicles or smart grids.

– Explainable AI: Researching methods to make AI systems more transparent and interpretable, enabling users to understand the underlying reasoning behind their decisions and actions.

– AI Ethics and Fairness: Investigating the societal impacts of AI, including ethical considerations, biases, and fairness in AI algorithms and systems.