BSc Data Science
About this course
Data science at UCL sits within one of the world's leading research universities, and the programme reflects that: it is mathematically rigorous, computationally demanding, and oriented toward the frontiers of what is currently known and possible in the field. Data science draws on statistics, machine learning, computer science, and domain knowledge to extract insight from large and complex datasets, and it is transforming almost every area of human activity from medicine and climate science to finance and the arts. This three-year full-time programme demands a high level of mathematical preparation and intellectual commitment. You will study probability and statistical theory, linear algebra, machine learning methods, algorithms and data structures, and the computational tools, primarily Python and related libraries, that are standard in professional and research practice. The programme develops your ability to formulate problems rigorously, choose appropriate methods, implement them correctly, and interpret and communicate your results with honesty and precision. You will engage with real datasets and applied problems, but always with a theoretical foundation that allows you to understand why methods work and where their limits lie. UCL's location in London puts you close to a major data science ecosystem spanning finance, technology, healthcare, and the creative industries. Graduates from this programme are exceptionally well placed for careers in data science, machine learning engineering, quantitative research, statistical analysis, and academic research. Employers range from global technology companies and investment banks to healthcare institutions and government departments. Many graduates pursue postgraduate study, including master's degrees in statistics, machine learning, and artificial intelligence, or doctoral research in areas where UCL is internationally recognised. The rigour of this programme means its graduates are competitive at the highest levels of both industry and academia.
Syllabus & Modules
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