Sri Lanka Institute of Information Technology (SLIT)

What you'll study

The curriculum starts with computing fundamentals and moves into databases, statistics and AI in the second year, then advances to intelligent agents, machine learning and deep learning in the third year, and finishes with applied AI topics in the fourth year.

• Year 1: fundamentals of computing, mathematics, data structures, algorithms, programming, technical writing and software engineering.
• Year 2: databases, statistics, AI and machine learning, industry project.
• Year 3: intelligent agents, machine learning, deep learning, bio-inspired computing.
• Year 4: MLOps, responsible AI, Edge AI, big data and data analytics, natural language processing.

Sample semester modules (first year):

• IT1120 Introduction to Programming (4 credits)
• IE1030 Data Communication Networks (4 credits)
• IT1130 Mathematics for Computing (4 credits)
• IT1140 Fundamentals of Computing (4 credits)
• IT1160 Discrete Mathematics (4 credits)
• IT1170 Data Structures and Algorithms (4 credits)
• SE1010 Software Engineering (4 credits)
• IT1150 Technical Writing (4 credits)

Students gain hands-on experience in languages and frameworks noted by the programme, including Python, R, Java, TensorFlow and PyTorch, and are exposed to Responsible AI, Edge AI and MLOps practices.

Entry requirements

Applicants must satisfy SLIIT/UGC/MOE-approved entry criteria. For local GCE A/Ls: a minimum of three ‘S’ passes in the Physical Sciences or Engineering Technology streams in one sitting, or three ‘S’ passes in any other stream plus a ‘C’ pass for O/L Mathematics and completion of the SLIIT IT Bridging Programme (exemptions apply for those who took ICT at A/L and have O/L Math ‘C’). For Cambridge/Edexcel A/Ls: minimum three ‘D’ passes in mathematics-related subjects or three ‘D’ passes in other subjects plus O/L Mathematics ‘C’ and completion of the IT Bridging Programme (similar exemption for IT/Computer Science A/L). Applicants must also pass the SLIIT aptitude test. To continue into the AI specialisation, students must meet the faculty’s minimum GPA at the end of Year 2 Semester 1.

Career prospects

Graduates are prepared for roles across AI and data-driven technology, including Machine Learning Engineer, Data Scientist, AI/ML Developer, AI Product Manager, NLP Specialist, Computer Vision Specialist, AI Solutions Architect and Big Data Engineer. The programme emphasizes industry readiness through projects, placements and professional certification opportunities.

Scholarships & funding angle

The course page does not list specific scholarships. Prospective students should contact SLIIT’s admissions or finance office to inquire about available scholarships, fee concessions, government or private funding and any merit-based support aligned with faculty policies.