Queen Mary University of London
Big Data Science
You should have a 2nd-Class degree or above (good 2.1 minimum for Industrial Experience option) in electronic engineering, computer science, mathematics, or a related discipline. Applicants with unrelated degrees will be considered if there is evidence of equivalent industrial experience. For international students whose 1st language is not English, we require English language qualifications IELTS 6.5 or TOEFL 92 (internet based) or equivalent qualification.
The MSc modules cover the following aspects: Statistical Data Modelling, data visualization and prediction; machine Learning techniques for cluster detection, and automated classification; big data processing techniques for processing massive amounts of data; domain-specific techniques for applying data science to different domains: Computer vision, social network analysis, bio engineering, intelligent sensing and internet of things; use case-based projects that show the practical application of the skills in real industrial and research scenarios. Students will be offered lectures that explain the core concepts, techniques and tools required for large-scale data analysis. Laboratory sessions and tutorials will put these elements to practice through the execution of use cases extracted from real domains. Students will also undertake a large project where they will demonstrate the application of Data Science skills in a complex scenario.
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