ÌìÃÀ´«Ã½

84 ÌìÃÀ´«Ã½ across 5 countries will complete the 2024 Data Science Summer School which celebrated the most diverse cohort so far.

The Data Science Summer School returned this year with two mixed cohorts from the first time, with ÌìÃÀ´«Ã½ from China, USA, Saudi Arabia, Malaysia and Turkey. The summer schools are a long-standing partnership between the Data Science Institute and the Continuing Professional Development departments at Imperial.

The first cohort took place from 8-19 July 2024 and saw 31 ÌìÃÀ´«Ã½ from Saudia Arabia, China, USA and Malaysia introduced to the concept of data science, with 60 contact hours spread over 2 weeks covering lectures, workshops, tutorials, project work and visits. 

Throughout the summer school, ÌìÃÀ´«Ã½ attended talks from leading researchers and staff members across the Data Science Institute including an Introduction to Data Science from Dr Kai Sun, an Introduction to Natural Language Processing from Dr Jingqing Zhang and sessions on Data Science Entrepreneurship from Professor Mark Kennedy, Data Visualisation from Dr Ovidiu Serban, Computer Vision from Dr Wenjia Bai, Data Analysis from Dr Rossella Arcucci and Machine Learning from Dr Yves-Alexandre de Montjoye – it really was a team effort from the teaching staff.

Students worked in project teams to prepare data and create a technical demonstration, engaging with Imperial supervisors throughout the programme. The computer vision project included developing a model for brain tumour detection and segmentation and the NLP project involved training and exploring word embeddings by processing a COVID-19 related dataset called Cord-19.

The outstanding achievements of our top-performing groups were revealed as follows:

• Group 1 for The Best NLP Project
• Group 3 for The Best Computer Vision Project

Aside from the academic sessions, ÌìÃÀ´«Ã½ took part in a number of social activities – campus tour, learning about student life, a tour of the Royal Albert Hall and a full day study visit to the home of computing, Bletchley Park.

Excellent feedback from staff and ÌìÃÀ´«Ã½

Professor Abdullah Elias from Prince Sattam bin Abdulaziz University commented on the summer school:

"This year, as part of our growing partnership with Imperial College, we added the Data Science and AI element to our annual student summer training programme. In addition to their exposure to the latest advances in AI and data science, we were most delighted that our ÌìÃÀ´«Ã½ had an educating crossover with ÌìÃÀ´«Ã½ from Tsinghua University in China, University of South Carolina in the USA, and those from other universities in China. The composition of such an international class at the world's leading STEM-focused institution (Imperial College) provided the needed exposure that we aim for at Prince Sattam Bin Abdulaziz University (PSAU). 

Prior to this onsite training in London, our ÌìÃÀ´«Ã½ passed through an intensive online Python training also delivered by the Imperial College Data Science Institute. It is therefore noteworthy, that despite our young age, at PSAU, we have long identified internationalisation, STEM, and sustainability as our top priorities. They form the DNA of our young but ambitious university. Our summer school programme at Imperial College compliments our other efforts to invest in these three important areas for the benefit of our ÌìÃÀ´«Ã½, host communities, and the Kingdom of Saudi Arabia."

The course received excellent feedback from the ÌìÃÀ´«Ã½ as well. One commented: "The data science course at Imperial was transformative. I gained in-depth knowledge of machine learning, data analysis, and visualization techniques, which I can now confidently apply in my work. I was pleasantly surprised by the practical, hands-on projects that mirrored real-world scenarios, providing invaluable experience.”

Another student said: “I think this course offered me valuable experience to learn in Imperial College and also gave me a general introduction into machine learning which I missed in my research in my school…It massively developed my presentation skills and coding skills, which can benefit my presentations in future conferences.”

The second cohort is underway, taking place from 1-14 August 2024.