Sri Lanka Institute of Information Technology (SLIT)

What you'll study

The curriculum builds from computing and mathematics fundamentals to advanced data science topics and applied research. Core themes include programming, data structures and algorithms, databases, statistics, AI and machine learning, deep learning, data warehousing, business intelligence, cloud computing, MLOps, natural language processing, database administration, data governance and data security. Practical learning features collaborative development with industry, real-world data projects and a research project in the final year.

Typical first- and second-year subjects are:

• Introduction to Programming; Fundamentals of Computing; Mathematics for Computing; Data Structures and Algorithms; Discrete Mathematics; Technical Writing; Software Engineering; Data Communication Networks
• Second-year focus includes databases, statistics, AI and machine learning and an industry project

Third- and fourth-year emphasis includes statistical modelling, deep learning, data warehousing, business intelligence, cloud computing, industrial training, research methodologies, MLOps, natural language processing, database administration, data governance, data security and a research project.

Entry requirements

Applicants must pass the SLIIT aptitude test. Local GCE A/L applicants need a minimum of three "S" passes in the Physical Sciences or Engineering Technology stream; alternatively three "S" passes in any other stream plus a C pass at O/L Mathematics and completion of SLIIT's IT Bridging Programme. Cambridge/Edexcel A/L applicants require three "D" passes in mathematics-related subjects or three "D" passes in other subjects plus a C at O/L Mathematics and completion of the IT Bridging Programme. Candidates who took Information & Communication Technology (local A/L) or Information Technology/Computer Science (Cambridge/Edexcel A/L) and have a C at O/L Mathematics are exempt from the IT Bridging Programme. Students must complete all modules up to year 2 to progress to year 3.

Career prospects

Graduates are prepared for roles that apply data and AI to solve business problems. Typical occupations named by the programme include Data Scientist, Data Analyst, Data Engineer, Machine Learning Engineer, Business Intelligence Analyst, Cloud Engineer, AI Specialist and Big Data Engineer across a range of sectors.

Scholarships & funding angle

The programme page does not list specific scholarships. Prospective students should explore institutional scholarships at SLIIT, government funding schemes and industry-sponsored internships tied to the mandatory placement to offset costs; contact the admissions office for current funding options.