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The two-year MSc Data Science program provides comprehensive training to derive meaningful insights from large datasets, preparing you for success across diverse industries. Designed for graduates from non-computing backgrounds - whether in sciences, technology, mathematics, or arts - this conversion program offers a unique gateway into the demanding world of data science. Our curriculum delivers both theoretical foundations and hands-on experience in handling complex 'Big Data' systems, teaching you to model, store, and process massive datasets using state-of-the-art algorithms. The program includes modern data visualization techniques and offers specialized elective modules to support your development as a professional data scientist.Why Choose Heriot-Watt?Our Data Science MSc provides industry-relevant expertise to launch your career:Academic Recognition: Ranked 6th in Scotland for Computer Science by The Complete University Guide 2022.Employer-Aligned Curriculum: Developed in consultation with industry leaders to teach exactly the skills employers value most in data science professionals.Technical Proficiency: Gain expert command of essential tools including Python, R, SQL, and data visualization platforms - critical skills for today's job market.Integrated Learning Approach: Our optimized curriculum creates strong connections between statistics, machine learning, and big data engineering, enabling you to solve complex data problems effectively.
Admission requires an honours degree at UK 2:2 level (minimum), with evidence of numeracy and familiarity with a programming language. This programme is designed for students with a non-Computer Science background who would benefit from a foundational year to help them to make a successful transition into Data Science. Therefore students will only be recruited into Year 1 of this programme. There is no direct entry into Year 2 of this programme. The minimum English language requirement for entry to this programme is IELTS 6.0 (or equivalent) with no score lower than 5.5.