Consistently rated amongst the world's best universities (4th in Europe and 9th in World, QS World University Rankings 2020), Imperial College London is a science-based institution with an international reputation for excellence in teaching and research. Imperial attracts over 17,000 students and 8,000 staff of the highest international quality from over 136 different countries.
Since its foundation in 1907, Imperial's contributions to society have included the discovery of penicillin, the development of holography and the foundations of fibre optics. This commitment to the application of research for the benefit of all continues today, with current areas of focus including interdisciplinary collaborations to improve global health, tackle climate change, develop sustainable sources of energy, address security challenges, develop data management and analysis technologies for supporting data driven research, and tackling problems at molecular scale.
Imperial’s Centre for Continuing Professional Development had extensive experience in developing and running a range of online winter schools for undergraduate students. We draw on Imperial’s education pedagogy in online learning to design and deliver winter schools that provide an engaging learning experience for students. Various interactive applications are used to support live teaching, online group projects are designed to assess students’ learning outcomes and virtual social platform created in Flipgrid will provide students with a networking environment.
The Data Science Institute (DSI) is a major Imperial College London initiative that brings together Imperial’s existing data science activities and expertise which provides a focus and a catalyst for new partnerships.
The DSI supports multidisciplinary collaborations between the College’s academic experts in many disciplines such as healthcare, financial services, climate science, and city infrastructure to create solutions to complex problems. Alongside research, the Institute fosters the next generation of data scientists and engineers by developing a range of postgraduate and executive courses.
The DSI includes 7 Academic Labs, has attracted over £50m in funding for data science research, technology and infrastructure and has published over 300 papers.
The Institute’s Data Observatory (DO) was one of the first and largest visualisation suites in Europe. It provides a multi-dimensional and immersive environment to analyse large and complex data sets.
Thanks to its many research collaborations both across College and with a variety of external academic and industrial partners, the DSI is establishing its role as an international hub in data science.
Data Science is successfully adding value to all the business models by using statistics and deep learning to make better decisions. A growing number of companies are now hiring data scientists to crunch data and predict possible situations and risk for businesses.
This online winter school is designed for undergraduate students studying IT, computing or any engineering degrees at a well-recognised university in China, with an interest in data science. Students will be introduced to the concept, develop an understanding of data science, hear from industry expert on data science applications and work in teams towards a technical project.
Learn the concept of Data Science;
Develop an understanding of data analysis, AI, machine learning for data science, exploratory data analysis and visualization;
Understand the real-world applications in data science and hear from industry expert;
Get an insight into advances in data science;
Gain an understanding of data privacy and ethics;
Learn from research experts in data economy and block chain;
Develop valuable professional skills in team building, communication and presentation;
Experience team-based learning through a technical data science project;
Practice and improve their English language.
Gain an understanding of the British Culture and visit to London Landmarks through virtual social activities.
Students will be working in project teams to prepare data and create a technical demonstration, engaging with Imperial supervisors throughout the programme. Previous projects include developing a model for brain tumour detection. Students will learn to prepare, transform and clean the dataset, as well as visualise the big data and their findings on the dataset.
In addition, students will have an opportunity to take part in virtual social activities, meet and discuss with Imperial ambassadors online, sharing their experiences on what it is like to study in a world class university and to discuss opportunities for future study.
43 learning hours spread over 3 weeks covering live lectures, workshops, tutorials, project work and self-study time.
Project work will be done through team-based learning with supervision. Final project will be presented in groups to a panel of experts on the final day of the programme. A prize will be awarded to the team with the best project.
The programme will be delivered over Microsoft Teams. Online project channels will be allocated to each team for project work and tutorials. Students will be able to use the channel at any time to work on their project.
Live classes of between 1.5 to 2 hours duration will be delivered on weekdays over a three-week period. Some days will have an additional one-hour live tutorial session with a project supervisor. All classes will be delivered between 08:30 to 11:00 UK time / 14:30 to 19:00 China time.
The entire programme will be taught in English.
All students are expected to be studying an undergraduate degree in any engineering discipline, IT or computing degree at a well-recognised university in China.
All students are required to have a good command of English, and if it is not their first language, they will need to satisfy the College requirement as follows:
a minimum score of IELTS (Academic Test) 6.5 overall (with no less than 6.0 in any element) or equivalent.
TOEFL (iBT) 92 overall (minimum 20 in all elements)
CET- 4 (China) minimum score of 550
CET- 6 (China) minimum score of 520
Technical knowledge requirements:
As the project has a strong technical element, students are expected to have the following technical knowledge and interest:
Interested in computer visualisation / natural language processing
Have at least intermediate level at one of the common programming language (Python, Java, C ++, etc.);
Have mathematical foundation (probability theory, linear algebra, etc.);
Have understanding of the Linux environment;
Knowledge of Machine Learning knowledge with experience in using PyTorch / Tensorflow / Keras.
Students will need to have access to a computer pre-installed with python, have a webcam, microphone and good internet connection to attend the live classes.
“I really have learned a lot through the programme and thanks to all professors, supervisors” - student from Shanghai Jiaotong University
“High quality teaching, useful knowledge and full support” - student from Shanghai Jiaotong University
“Wonderful. Enhance my understanding of data science. It is also wonderful to listen and discuss opinions with the professors” – student from Zhejiang University
“It's indeed a wonderful experience, learning knowledge and coming across with so many excellent teachers and classmates” -student from Zhejiang University
“This programme opens a door to the world of data science for me! Brilliant!” - student from Zhejiang University