• 专业概况
• 所属院系
• 中国学生入学要求
• 课程信息

专业概况

在这里学什么？

The MSc Environmental Data Science and Machine Learning will educate future environmental scientists in data science, machine learning and associated computational technologies. This course will deepen your knowledge of cutting-edge data science, machine learning and associated computational and observational techniques, and you will learn to apply this to a broad range of environmentally motivated applications.

If you have:

• a strong methodological background in mathematics or physical sciences and you're interested in moving to an applied field with an environmental slant or;
• an applied background in environmental science or engineering and you want to learn about data science and machine learning or;
• a background in computer science and you want to expand your knowledge of applied data science and machine learning in an environmental context, you're encouraged to apply.

The Environmental Data Science and Machine Learning MSc programme will teach you to apply data science and machine learning knowledge, and computational modelling and monitoring techniques, to a range of environmental science and engineering applications.

Graduates of this course will be equipped with the skills required for the next generation of environmental scientists and engineers. Through the multidisciplinary focus of computational knowledge and techniques, within the context of solving environmental science problems, you will be able to pursue further research in any of these fields or move into careers in fields such as climate science, sustainability, natural hazards and renewable energy.

所属院系

进入哪个院系学习？ Department of Engineering

中国学生入学要求

为来自中国的学生设计 Students should have been awarded a Bachelor's degree from Project 211 university with a final overall mark of 80% or better. Preference is given to candidates with 85% or better.

课程信息

学制：全日制(1 年)

学费：£34,750.00 (¥ 313,789) /年

开学时间：2022十月4日

申请截止日期：

留学地点：South Kensington CampusExhibition Road,Kensington and Chelsea,London,SW7 2AZ, England