帝国理工学院健康数据分析和机器学习专业项目网站

Health Data Analytics and Machine Learning

英国公立健康

项目背景

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更新时间:2024-07-29

专业排名N/A

大学帝国理工学院

开学时间10月

课程学制1年

学费40800.00/GBP

专业介绍

Our MSc in Health Data Analytics and Machine Learning is a one-year full-time course aimed at building a solid and common background in analysing health data. Your main objective is to develop skills in using appropriate cutting edge quantitative methods to fully exploit complex and high dimensional data. The course is delivered in collaboration with the Data Science Institute, with teaching from both the School and Institute undertaken by international experts with strong methodological background and expertise in the application of these approaches to large-scale medical and clinical data. The programme features extensive project-based learning using real data sets and addressing real scientific questions through module-specific projects work, and individual research projects. This Master’s is integrated in the research priorities of the School of Public Health, the Data Science Institute, the MRC Centre for Environment and Health, the UK Dementia Research Institute, and the pan-London Health Data Research UK initiative, through: the contribution to teaching of key staff members (lectures, seminars, journal clubs) the definition of research projects stemming from data available and yet under-exploited in each institute As such, not only the programme will equip students with cutting-edge statistical and machine learning techniques that are required to explore emerging ‘Big’ health data, but will also provide extensive experience in their application in a real-life setting in Environmental, Molecular, Cancer, and Computational epidemiology as well as in Population and Health sciences. Throughout, teaching will include project-based work. Projects are based on real data and will address real scientific questions from research staff within School of Public Health, Data Science Institute and industrial partners.

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语言要求

类型
雅思
托福
PTE
Listen
6.5
22
62
Speak
6.5
22
62
Read
6.5
22
62
Write
6.5
22
62
总分
7
100
69

学术要求

领域:数学,统计,流行病,生物或医学类专业

课程设置

Introduction to Statistical Thinking and Data Analysis:统计思维与数据分析导论 Principles and Methods of Epidemiology: 流行病学原理与方法 Molecular Epidemiology: 分子流行病学 Translational Data Science Part and: 转化数据科学部分和 Clinical Data Management: 临床数据管理 Machine Learning: 机器学习 Computational Epidemiology: 计算流行病学 Advanced Analytics: 高级分析 Population Health Analytics: 人口健康分析

申请案例

学生姓名:戴 **

毕业学校:南安普顿大学

本科专业:CS

基本背景:/GPA82/100/雅思0