The Best Data Science Summer Programs for High School Students

One of the fastest-growing career niches in the 21st century, data science is an interdisciplinary field that utilizes skills in mathematics, statistics, and computer science to analyze data, identify patterns, and solve problems across various industries.

It’s hard to think of a field that doesn’t use data in some regard. The healthcare, education, and criminal justice system immediately come to mind, while tourism bureaus, financial advisors, and airlines additionally rely on data to understand their clientele, anticipate the need for new products and services, and predict future obstacles and opportunities.

Not only does participation in a data science summer program prepare you for the rigor of a collegiate data science course sequence; additionally, it exposes scholars to the wide range of careers where data science skills apply. 

An added benefit entails working alongside expert data science academic instructors and industry professionals who can potentially serve as contacts for letters of recommendation during the college admissions (or job application) processes.

When applying for summer programs in data science programs, you can select between in-person and virtual experiences, many of which advertise scholarships for different demographics. 

We have compiled a list of 10 of the best data science summer programs for high school students in the United States, with many options offering new courses annually. 

Syracuse University Data Visualization and Analysis (Syracuse, NY)

Syracuse University
Public domain photo via Wikimedia Commons

A typical day at the Syracuse Data Visualization and Analysis summer program immerses students in hands-on morning workshops and afternoons dedicated to collaborative laboratory projects. Participants will gain exposure to tools like Microsoft Excel and Tableau to learn how to input and manipulate data and perform higher-level analytical functions for critical decision-making in various industries.

At any given time, students will work independently and in groups to understand how to respond to unknown data sets, explore data through visual mechanisms and clean up data to prepare it for analysis. 

Additionally, they will become proficient in computing basic statistics to acquire meaningful insights, then have opportunities to present data to mock stakeholders.

The experience is open to resident or commuter participants who qualify as rising high school sophomores, juniors, or seniors – recent high school graduates are also eligible to apply. 

The program operates on a rolling admission system, so early application submission is suggested. All course completers will receive a certificate and receive guidance for requesting a Syracuse University noncredit transcript.

The Carnegie Mellon University Pre-College AP/EA Data Science Experience (Pittsburgh, PA)

Carnegie Mellon University
Dllu, Gates-Hillman Complex at Carnegie Mellon University 3, CC BY-SA 4.0

The Data Science Experience takes place at the #3 ranked undergraduate institution for data science in the United States: Carnegie Mellon University. 

Led by faculty from the school’s Department of Statistics & Data Science, this program provides an outstanding opportunity to prepare for a rigorous collegiate data science curriculum.

In this exciting experience, high school participants enroll in two college-level classes and take part in existing research projects that require analyzing data sets, coding data, and using other essential software to glean key insights from large troves of information.

What kind of information will participants examine? Existing data sets include 500 randomly chosen flights, two years of Capital Bike Share information, nutritional content from over 4,000 distinct foods, and information regarding NYC housing conditions across the five boroughs.

Supplemental activities keep things challenging and entertaining. Students engage in get-to-know-you games via social network analysis, use image analysis to characterize the historical evolution of architecture, and meet with professional sports analysts in dynamic workshops. Guest speakers from Google, RAND, and Disney Research make regular appearances. 

Quinnipiac University Computing and Data Sciences for High School Students (Hamden, CT)

The two-week data science program at Quinnipiac balances theoretical knowledge with real-world applications, prioritizing ways in which participants can pursue diverse career options with their acquired data science skills. 

The ideal applicant gravitates to complex problems, enjoys searching for elusive patterns, demonstrates creative thinking, and jumps at the chance to become adept in new technologies.

A typical morning begins with an introduction to the daily theme, a motivational game, and a morning lesson. 

In the afternoon, students engage in project collaboration focusing on authentic data sets, where they’re charged with detecting patterns and coming up with novel solutions. The evenings are reserved for fun social and recreational activities, though applicants can leave as commuters at the end of the afternoon session.

Regardless of which option scholars select, they will receive a certificate of completion, a Quinnipiac t-shirt, one-on-one tech support, and exclusive access to Quinnipiac admissions events throughout the year. Only those ages 15 to 18 may apply, and each participant must bring a laptop computer.

The University of Chicago Data Science Institute Summer Laboratory (Chicago, IL)

Are you hoping for a chance to conduct some summer research? Look no further than U of Chicago, where the Data Science Institute Summer Lab program – newly launched in 2018 – promises an accelerated ten-week paid research internship for both high school and undergraduate enrollees. 

Each accepted candidate will be paired with a data science faculty mentor from one of several domains, including climate and energy policy, materials science, and biomedical research. 

Teams will unite to improve their techniques in quantitative analysis and need not have any previous research experience to apply.

Each participant will create a final video, which they will present to their peers and mentors at the end-of-summer symposium. 

Similar to a professional conference, the symposium represents an opportunity for students to share exciting discoveries and field questions about the significance and limitations of their inquiry. Many alumni of the DSI maintain a congenial rapport with their mentors after the program concludes.

The University of Washington AI4ALL at the Paul G. Allen School (Seattle, WA)

AI4ALL is a national nonprofit with enrichment programs dedicated to fostering diversity and inclusion within the fields of artificial intelligence (AI) research, development, and policy-making. 

More than 10,000 participants have completed AI4ALL programs throughout all 50 states and in other areas of the world.

The University of Washington’s AI4ALL chapter is unique in its emphasis on the intersection of AI and data science. The free, two-week workshop takes place at U of Washington’s Taskar Center for Accessible Technology and is open to rising high school juniors, seniors, and college first-years. 

Participants can anticipate working in intimate, diverse groups in collaboration with current researchers in statistics, engineering, mathematics, and computer science. Major curricular themes place complexity, robustness, closed-loop data science, and ethics and algorithms at the center of all learning activities. Curriculum objectives include data analysis and interpretation and Socratic discussion revolving around decision-making consequences that stem from data sets.

Stanford Pre-College Summer Institutes: Introduction to Data Science (Virtual)

Tied for 4th place in the U.S. News ranking of best undergraduate data science programs, Stanford University’s Pre-Collegiate Sumer Institute – focusing on data science – provides an unparalleled opportunity to work with some of the best data science practitioners in the field. 

In general, the summer institutes boast small class sizes and over 50 course offerings, all of which are conducted in synchronous online environments.

There are two 12-day sessions available for high school students in grades 9-11. Morning classes run from 8-11 AM, and afternoon sessions take place from 4-7 PM. 

In addition to six daily hours of class time, scholars engage in asynchronous work, such as designated readings, collaborative projects, online lectures, and more. As you can discern, this data science summer program requires a high level of time commitment!

To participate, applicants must have completed either AP Statistics or a computer science course at the high school level. 

In the Stanford course, students will explore complicated computer algorithms and generate their own. They will use datasets from the realms of natural and social sciences and apply various aspects of machine learning through R programming to make meaning from the data.

Wharton Global Youth Program Data Science Academy at The University of Pennsylvania (Philadelphia, PA)

The Wharton School of the University of Pennsylvania
Public domain photo via Wikimedia Commons

The Data Science Academy at Wharton places a double emphasis on merging critical thinking with foundational knowledge in statistics. Participants will be able to utilize some of the most cutting-edge machine learning and data science tools and software programs of today. 

In the previous program description, we mentioned the R language, one of the most popular languages used by working data scientists. Students at Penn will also learn and use this language in their endeavors. 

Approximately 71 exceptional high school sophomores and juniors will be accepted into the DSA upon demonstrating an extensive background in coding, mathematics, and statistics.

A typical day at the DSA entails morning current events discussions and lectures followed by afternoon guest speaker lectures and group work. 

Topics cover the processes of acquiring, cleaning up, investigating, and visualizing data. In the evenings, students have the freedom to dedicate time to their final projects, meet with faculty and teaching assistants, or relax in the dormitories.

Code Connects Virtual Summer Camps (Virtual)

Code Connects boasts one of the best reputations for virtual computer science summer camps, being that they’re designed by engineers from successful companies like Microsoft, Google, and Disney, along with faculty from Harvard, Brown, and Stanford. 

New camps are announced every February for scholars in grades 6-12 and first-year college students, though many signature experiences carry over from year to year. 

Emerging Tech is one of Code Connects’ flagship programs, aiming to cultivate student expertise in AI, web development, cybersecurity, healthcare, and technology. In the span of two weeks, participants learn coding skills that they likely wouldn’t have exposure to in a high school setting. 

Week one prioritizes Python and additional related concepts, such as booleans, loops, conditions, and functions. In week two, participants apply their knowledge toward a final project in a field of interest – previous examples include asymmetric encryptions and pet simulators.

Another camp – AI & Big Data – prompts students to train their computers to build smart machines using machine learning and AI skills. Learn the secrets of how movie streaming services understand users’ preferences and how self-driving cars can operate safely! Bias mitigation in machine learning is a critical element of this curriculum.

UCLA Computer Science Summer Institute – Introductory Track (Los Angeles, CA)

Are you ready to participate in a Hackathon?! If you aren’t now, you will be by the conclusion of this three-week in-person data science summer program for students entering grades 8-12 in the spring. 

One of the ultimate benefits of participation is the opportunity to earn up to four units of computer science credit at UCLA! No prior experience is required, making this a truly accessible option.

Some of the critical topics of the computer science intro sequence include data types like integers, lists, and strings, as well as control structures and functional decomposition. Participants will use Python as their primary coding language.

Morning and afternoon sessions are typically three hours long and taught by UCLA professors or undergraduate tutors. 

In the beginning, students will learn what programs are made of and common elements across programming languages. 

As the curriculum progresses, they’ll learn about recursive functions and encounter tasks requiring them to sort algorithms. The Hackathon takes place on the last day, and you’ll have to attend to find out what all the talk is about!

Python Data Science & Machine Learning Program (New York City, NY)

Arguably the best of its kind in the United States, the Python Data Science & Machine Learning Program encompasses two weeks, with participants dedicated at least six hours daily to learning Python fundamentals before transitioning to more advanced coursework. 

Using software like Pandas, Sci-Kit, and Matplotlib, scholars will quickly learn how to input, interpret, and visualize data.

Program tuition includes all required hardware and software, connections with experienced professors and industry pros, additional online supplemental activities, and small in-person class environments. 

Exciting projects keep participants engaged and curious. One group might work on developing vector maps to measure heat sensitivity, while another may track inflation from the 1800s to the present day.