项目背景
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更新时间:2024-07-08
开学时间9月
课程学制1年
学费37368.00/GBP
专业介绍
The Applied Statistical Modelling and Health Informatics course has been created to deliver a skill set and knowledge base in "multimodal" and "big data" analysis techniques, which are a recognised scarcity within UK Life sciences. You will receive world-class training in core applied statistical methodology, machine learning and computational methodology, and you will have the opportunity to apply your skills to real-life settings facilitated by the world-leading Institute of Psychiatry, Psychology & Neuroscience. The course will apply to a broad spectrum of graduates preparing for a career in medical statistics and health informatics, or professional methodologists and clinical researchers working in the private or public health sector who are interested in state-of-the-art technologies training from world-class experts. This course is also suitable if you are a graduate in/work in the fields of computer science, maths, physics, engineering and natural science, including psychology and medicine. The course will prepare participants for the ever-growing need for a sound scientific approach to processing information and generating knowledge in modern health services. Practical skills will be taught through applications to real-life settings in a world-leading research institution in mental health
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语言要求
Write
6.5
25
62
总分
7
100
69
学术要求
专业领域:计算机科学,数学,统计学,物理,Natural Sciences, 电子工程,心理学或GIS地理信息系统。
课程设置
Required modules:所需模块 MSc: MSc Introduction to Statistical Modelling: 统计建模简介 Introduction to Statistical Programming: 统计编程简介 Introduction to Health Informatics: 健康信息学简介 ASMHI Research Project For MSc only: 仅面向MSc的ASMHI研究项目 PG Dip: PG Dip Introduction to Statistical Modelling: 统计建模简介 Introduction to Statistical Programming: 统计编程简介 Introduction to Health Informatics: 健康信息学 PG Cert: PG Cert Introduction to Statistical Modelling: 统计建模简介 Introduction to Statistical Programming: 统计编程简介 Optional modules: 可选模块 Multilevel and Longitudinal Modelling: 多级和纵向建模 Prediction Modelling: 预测建模 Causal Modelling and Evaluation: 因果建模和评估 Machine Learning for Health and Bioinformatics: 健康和生物信息学机器学习 Clinical trials A practical approach: 临床试验A实用方法 Natural Language Processing NLP: 自然语言处理NLP Contemporary Psychometrics: 当代心理计量学 Introduction to Computational Neuroscience: 计算神经科学简介 Structural Equation Modelling SEM: 结构方程建模SEM Artificial Intelligence in Health Analytics: 健康分析中的人工智能 Bioinformatics Interpretation and Data Quality in Genome Analysis: 基因组分析中的生物信息学解释和数据质量 Advanced Bioinformatics Practical Bioinformatics Data Skills: 高级生物信息学实用生物信息学数据技能