Data Science Summer Academy

Program period:
July 22 to August 9, 2024

Data Science Institute (DSI), The University of Chicago
The University of Chicago Francis and Rose Yuen Campus in Hong Kong

The University of Chicago Francis and Rose Yuen Campus in Hong Kong
168 Victoria Road
Mount Davis, Hong Kong Island
Hong Kong SAR


Have you ever wondered what you can do with data? How can you store it, manipulate it, or visualize it? What does it tell us?  How can you start to analyze it? How can you extract meaning and value from it?

During the Data Science Summer Academy, you will gain insight into these questions through a series of lectures, labs, and activities and will have the opportunity to learn from guest speakers.

In particular, this summer program will introduce students to all aspects of a data analysis process through a collection of case studies, from posing questions, designing data collection strategies, management, storing and processing of data, exploratory tools and visualization, statistical inference, prediction, classification, machine learning, and interpretation and communication of results. Computation will be done using Python and Jupyter Notebooks.

The program will culminate with a capstone project which will give teams of students the chance to showcase what they learn.

Please note that participation in the Data Science Summer Academy in Hong Kong is not a guarantee of admission into the University of Chicago.


  • DSI Preceptors are data science experts leading the lectures and providing support in students’ learning journey
  • Students will have a better understanding of data and its application in the real world, along with projects that students can include in any of their college applications
  • Guest speakers who will share their insights in data science as a career
  • Excursions to relevant industries and sites to advance students’ understanding of data science applications
  • Available for current high school students who are at least 15 years old
  • Students with a strong background in math (minimum knowledge – Algebra I), statistics and coding, and interest in data analytics
  • The program's medium of instruction will be in English, so students should be comfortable in an English-speaking learning environment
  • Applicants must be Hong Kong residents or be eligible to study in Hong Kong during the program period

In preparation for the course, students will be expected to complete some coursework to familiarize themselves with some common concepts and theories related to the course. Students are expected to bring their own laptops to class and will also be provided with instructions on how to download the Jupyter Notebook software, which will be used frequently in this course.

Academic classes are held Monday through Friday with excursions planned on Wednesdays. Guest speakers will be integrated into the classes throughout the program. The last week of the program will be focused on group and individual works on a data sciences-related project.

While each day varies slightly in format, a typical day includes:

  • 9:30 to 10:45 – Lecture
  • 10:45 to 11:15 – Mid-morning break
  • 11:15 to 12:30 – Lecture
  • 12:30 to 13:30 – Lunch
  • 13:30 to 16:00 – Campus available for group or individual work
  • Introduction to Data Science
    • Introduce students to the data science pipeline
    • Develop students' abilities to be informed and critical readers of quantitative, data-based arguments
    • Methods of visualization and communication of data
    • Opportunity to analyze real world data
  • Coding experience with Python and Jupyter Notebooks
    • Enable students to perform data analysis using Python
    • Introduction to python libraries: NumPy, pandas, Scipy, Matplotlib
    • Develop students' abilities to integrate code, background information, results and interpretation in a Jupyter Notebook to communicate data analyses effectively
  • AI, Data Science and Machine Learning
    • Gain flexible problem-solving and programming skills applicable to a large variety of problems independently
    • Hands-on experience with prediction and classification algorithms
    • Feature engineering and one hot encoding
    • Overview of neural networks

Main Instructor of DSSA
Preceptor at the Data Science Institute

Susanna is a Preceptor in Data Science at the University of Chicago. She is working jointly with the University of Chicago and City Colleges of Chicago to teach data science courses at both institutions. She has experience teaching students of a wide variety of backgrounds and modalities and enjoys engaging students in the classroom. She recently graduated with a PhD in Mathematics with a research focus in machine learning working with Qiang Ye at the University of Kentucky. The focus of this research was on preconditioning methods for neural networks. Her current research focus lies in social impact projects and she has mentored projects working with Long-term memory neural networks and exploratory spatial analysis. She is excited to be a part of the Data Science Summer Academy 2024 in Hong Kong!

Faculty Director of DSSA
Elaine M. and Samuel D. Kersten, Jr. Distinguished Service Professor; Faculty Co-Director at the Data Science Institute

Dan Nicolae obtained his Ph.D. in statistics from The University of Chicago and has been a faculty at the same institution since 1999, with appointments in Statistics (since 1999) and Medicine (since 2006). He has served as chair of the Department of Statistics from 2016-2022, and section chief for the Section of Genetic Medicine from 2015-2016. His research seeks to understand the role of genetic, genomic and environmental factors, and their interactions, in the development of common/complex diseases. A statistical geneticist and a mathematical statistician, he specializes in developing methodological advances for large data problems in biology and medicine. Particular interests include functional genomics, microbiome, integration of omics data, networks, and systems biology. The statistical and computational methods developed by his group are based on foundations in high-dimensional statistical inference, machine learning and data science. 

The Data Science Institute (DSI) executes the University of Chicago’s bold, innovative vision of Data Science as a new discipline. It is part of an ambitious, multi-year expansion of computer and data science efforts at the University. DSI’s mission is to address important scientific and societal questions through coordinated advances in applications, models, algorithms and platforms, specifically, through research, outreach and education. The Data Science Summer Academy designed by DSI is one of it’s educational and outreach pursuits to training the next generation of data scientists.

Find out more about DSI here.

  • Early Bird Application Deadline: April 30, 2024
  • The Extended Application Deadline: June 17, 2024

1. Latest school transcript

2. Students’ statement of purpose

  • The statement of purpose should be a document of less than 700 words describing your interests as well as your background and why you would like to pursue a data science class this summer. You can address any of the following:
    • Explain why you would be a good fit for the Data Science Summer Academy. What skills and experiences do you have that would make you a good candidate?
    • What do you consider to be your greatest accomplishment?
    • Describe an experience that you believe has prepared you for the Data Science Summer Academy. This can be related to any extracurricular experiences, a class project, communication, leadership, etc.

3. [Optional] English Proficiency Scores

4. [Optional] Letter of Recommendations

5. [Optional] List of extracurricular activities and personal achievements

Application submitted:

Hong Kong Dollars

Before April 30, 2024


Between May 1 and June 17, 2024


Program fee includes the course fee, use of the UChicago Campus in Hong Kong facilities, one meal and refreshments during on-campus days, excursion expenses, and shuttle buses to and from campus and Kennedy Town MTR Station. Program Fees are non-refundable once paid unless the program is canceled by the UChicago campus in Hong Kong.

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