July, 2024

Xi'an, China

【Introduction】

Big data has received great attention in various disciplines and has become an important research direction in a number of disciplines such as computer science and statistics. The development of this field shows a deep integration of data research between different specialisations and is evolving into an emerging discipline, data science. Data science combines statistics, machine learning, and domain-specific knowledge, and is an emerging discipline based on these theoretical foundations. Among them, social data science integrates the theories, concepts and methods of social science and computational science, providing a new scientific perspective for studying social data.

【Course Professor】

Dr Charlie Rahal is an associate professor in computational social science at the University of Oxford, where he works with colleagues at the Demographic Science Unit and Leverhulme Centre for Demographic Science (where he forms part of the Senior Management Board). He is a co-investigator at the ESRC funded Centre for Care (and on another ESRC Strategic Research Grant), and acts as the local network lead co-ordinator for the UK Reproducibility Network (as part of the steering of Reproducible Research Oxford). He was previously a British Academy Postdoctoral Fellow. His training includes degrees, diplomas, and certificates in computational econometrics, economics, advanced research methods, and investment and finance.

His research focuses on methodological innovations which uncover patterns in large-scale observational data with a focus on equality and equity. It is usually motivated by a desire to improve policies and public administration. This most recently includes but is not limited to population-wide scientometric analysis, model evaluation in machine learning, and computational approaches to the life course (broadly defined). He has recently been involved in several successful funding applications (totalling around £12m) and has published in many of the world's leading journals. He predominantly works in Python, Bash and TeX, and takes great pride in being able to generate policy impact - having won awards and commendations for contributions to the UK government Covid-19 policy response - all through open and reproducible research.

【Curriculum system】

The course will be taught in a "real-time coding" format using the interactive "Jupyter Nootebooks" software, with the aim of enhancing students' practical ability to solve social data science problems. The expected outcome of the course is to enhance students' professional skills and theoretical knowledge of Big Data. The results of the project will be presented through the completion of large assignments by the students on their own.

Teaching Format: Offline teaching, Classroom 874 of Jinhe Center for Economic Research, 8^th Floor, Building of Management School.

Course Arrangement:

Additionally, Dr Charlie Rahal would be happy to provide a 1-2 hour pre-school tutorial where students can come to him for help installing the necessary tools. He can also provide a class handout in advance detailing how to install this and how to find all the lecture materials. All instructional materials will be freely and openly available. There will be an optional homework assignment at the end of each class, and these will be reviewed at the beginning of the next class.

【Registration】

Graduate or undergraduate students in the social sciences are eligible to apply. To ensure the quality of the course and real-time tutorial programming, the number of participants will be limited to 20-25. Students interested in applying for the summer school should email jinhe7879@xjtu.edu.cn.

Student Treatment: Xi'an Jiaotong University will provide a study stamped certificate (Certificate of Completion) for this summer course.

Contact Information:Weihong Zeng, jinhe7879@xjtu.edu.cn