MSc Computer Science (Artificial Intelligence)

Artificial intelligence (AI) is becoming increasingly vital in shaping advancements across business and society. The Department of Computer Science, University of Kerala has been doing active research in Machine Learning and Intelligent Systems, and AI related modules. The programme provides students with an understanding of AI concepts, techniques, and their real-world applications. It combines theoretical foundations with hands-on learning, covering machine learning, natural language processing, IoT, robotics, and computer vision. Students will gain the expertise needed to design and implement AI solutions.

Through a curriculum developed in collaboration with industry experts, the course enables critical thinking and problem-solving skills. Students will engage in practical projects, collaborative work, and research, preparing them to contribute to the growing AI field. The program also promotes professional ethics and societal responsibility in developing AI systems.

i.The basic theoretical understandings of machine learning, natural language processing, and computer vision, and their state-of-the-art system architectures.
ii.The possession of excellent skills in the design and implementation of Artificial intelligence systems with the help of Machine Learning and AI technologies.
iii. Concrete theoretical foundations in Artificial Intelligence and allied areas to enrich their abilities for employment or research in R&D institutions.
iv. The ability to understand, analyze and demonstrate the knowledge of human cognition, Knowledge, Artificial Intelligence, Machine Learning and data analysis to meet the challenges to intelligently solve real-life problems.
v. The ability to convert descriptions of abstract AI challenges into descriptions of specific AI project requirements.
vi. The ability to validate the performance and fine tune the AI based models.
vii. Capability to demonstrate the theoretical background and working of AI based systems like agents and expert systems taking some sample use cases.
viii. The ability to understand standard research publications in AI and ML, design and write the works scientifically for publishing.
ix. The knowledge in natural language processing and their advancements with the help of new generation ML methods so that capable of tracing the developments in NLP and information processing.
x. Practical knowledge of the basic theoretical concepts of AI and ML either in the form of working case studies or hands own exercises.
xi. The ability to understand the theoretical basics of the scientific process of designing machines that are capable of performing human-like thinking and inductive decision-making.
xii. Talent to understand the basics of different computational techniques and thereby find solutions and design optimized algorithms to improve computing performance