Artificial Intelligence and Data Science for Healthcare Innovation

Engage with Imperial academics "live" online!
1 to 14 February 2023

Artificial intelligence and data science have a pivotal role in driving a new era of innovation in many fields and they have the potential to transform businesses and industries.  

As the knowledge of data science and AI is successfully adding value to business innovations,  a growing number of organisations are now looking for these skills set in their recruitment.

This online winter school is designed for undergraduate students with NO coding knowledge, studying any subject disciplines, with an interest in learning the applications of AI and data science in businesses. 

Students will be introduced to the concept of data science and AI, hear from industry experts on these applications and learn basic Python coding to work in teams towards a group project.

Students will:

  • Develop an understanding of data science and AI’s application in various industries sectors and how they support business innovations.
  • Develop an understanding of data entrepreneurship.
  • Explain how machine learning is used for data analysis.
  • Understand how robotics and AI play an important role in engineering design.
  • Understand how data are presented using visualisation tools.
  • Understand how AI is used to assist electronic health records.
  • Explain blockchain technology and it’s applications.
  • Explain the importance of data privacy and ethics.
  • Apply basic coding in Python.
  • Identify valuable professional skills in team building, communication and presentation and apply on a team-based project.
  • Improve their English language.

In addition, students will participate in online social activities, meet new friends and hear about opportunities for international students at Imperial.

For registration, please contact:

A scholarship of up to £600 will be provided by Global University Online. To apply, please visit:

More information

Programme structures & format

40 learning hours spread over 10 weekdays covering live lectures, tutorials, project work and self-study time.

Live sessions of up to 4 hours’ duration will be delivered on weekdays.  Classes are delivered from 08:00 UK time / 16:00 China time.

Project work will be done through team-based learning with supervision. Final projects will be presented in groups to a panel of experts on the last day of the programme. A prize will be awarded to the team with the best project.

The programme will be delivered over Microsoft Teams and Zoom. Online project channels in MS Teams 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.

The entire programme will be taught in English.

Teaching faculty

The summer school is co-directed by Professor Yike Guo and taught by a multi-disciplinary teaching faculty from the Data Science Institute and other departments at Imperial College London.

Yike Guo

Yike Guo is Professor of Computing Science in the Department of Computing at Imperial College London. He is the founding Director of the Data Science Institute at Imperial College. He is a Fellow of the Royal Academy of Engineering (FREng), Member of Academia Europaea (MAE), Fellow of British Computer Society and a Trustee of The Royal Institution of Great Britain.

 Professor Guo received a first-class honours degree in Computing Science from Tsinghua University, China, in 1985 and received his PhD in Computational Logic from Imperial College in 1993 under the supervision of Professor John Darlington. He founded InforSense, a software company specialized in big data analysis for life science and medicine, and served as CEO for several years before the company's merger with IDBS, a global advanced R&D software provider, in 2009. He was then the Chief Innovation Officer of the IDBS until 2018. He also served as the Chief Technical Officer of the tranSMART foundation, a global alliance in building open source big data platform for translational medicine research.

He has been working on technology and platforms for scientific data analysis since the mid-1990s, where his research focuses on data mining, machine learning and large-scale data management. He has contributed to numerous major research projects including: the UK EPSRC platform project, Discovery Net; the Wellcome Trust-funded Biological Atlas of Insulin Resistance (BAIR); and the European Commission U-BIOPRED project. He was the Principal Investigator of the European Innovative Medicines Initiative (IMI) eTRIKS project, a €23M project building a cloud-based informatics platform, in which tranSMART is a core component for clinico-genomic medical research, and co-Investigator of Digital City Exchange, a £5.9M research programme exploring ways to digitally link utilities and services within smart cities.

Professor Guo has published over 250 articles, papers and reports. Projects he has contributed to have been internationally recognised, including winning the “Most Innovative Data Intensive Application Award” at the Supercomputing 2002 conference for Discovery Net, the Bio-IT World "Best Practices Award" for U-BIOPRED in 2014 and the "Best Open Source Software Award" from ACM SIGMM in 2017.


Students will receive a verified Imperial College London digital certificate on successful completion of the winter school and a prize will be awarded to the best project team. Each student will also receive a transcript for their project marks.

Entry requirements

All students are expected to be studying an undergraduate degree at a well-recognised university in China meeting the following entry requirements.

English requirements:

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

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. Guidance will be provided to students on installing python.

Students are NOT expected to have any technical coding skills.

This winter school is also suited for medicine students, willing to diversity their skill set.