What is your next education pathway?
The Foundation Course in Data Science is designed to provide students with a comprehensive introduction to the key concepts and tools used in data science. This course is ideal for individuals interested in pursuing careers in data analysis, machine learning, and business intelligence, equipping them with the foundational skills needed for success in the field.
Students will begin by exploring essential mathematical concepts, including Calculus and Linear Algebra, both of which are fundamental for understanding data modeling and analysis. The course also covers Business Statistics, providing students with the statistical tools necessary for data interpretation.
In addition to technical skills, students will develop proficiency in Business English for clear and professional communication, and gain an introduction to Business Management concepts to understand how data science can drive organizational success. Academic Writing skills will also be covered to support effective communication in research and academic settings.
Students will gain hands-on experience in Data Analysis using tools like Excel and SPSS, and learn programming basics in Python and R, two of the most widely used languages in data science.
By the end of the course, students will have a strong foundation in data science principles and tools, preparing them to advance their studies or pursue entry-level roles in the field.
Entry Requirements
G.C.E Ordinary Level or Cambridge Ordinary Level or EDEXCEL Ordinary Level Examinations (5 credit passes including Mathematics, English Language and Information Technology related subjects).
Commencement
Kirulapone (NIC) – Pending
Peradeniya (KIC) – Pending
Lecture Schedule
9.00 am to 4.00 pm (Wednesday, Thursday, Friday)
Programme Fees
Current Fee Structure
Course Fee: LKR 300,000 + Registration Fee: LKR 8,000
Student loan facilities are available from BOC, NSB & NDB banks. Send us an inquiry to ask about payment plans and loan facilities.
Course Structure and Modules
Introduction to Calculus for Data Science
Introduction to Linear Algebra for Data Science
Introduction to Business Statistics for Data Science
Business English
Introduction to Business Management
Academic Writing
Introduction to Finance
Introduction to Data Analysis using Excel and SPSS
Introduction to programming in Python
Introduction to programming in R
*Subjected to revision according to the industry requirements.