15 Data Analytics Summer Programs for High School Students
If you are a high school student interested in data analytics, a summer program can be a great start. Offered by reputable universities and organizations, data analytics programs let you dive into the world of analytics, coding, and problem-solving. Whether it’s a fast-paced boot camp or a research fellowship, these programs let you explore everything from the basics of stats and Python to advanced machine learning and AI. You'll get to develop tangible projects, enhance highly relevant skills, and start building a portfolio. They also provide you with opportunities to connect with industry professionals and peers, allowing you to begin developing your professional network at an early stage.
To make it easier for you, we’ve rounded up the 15 best Data Analytics summer programs for high school students.
1. Data Science Institute Summer Lab program
Location: University of Chicago, Chicago, Illinois
Stipend: $5,600
Acceptance Rate: Highly Selective
Dates: June 16 – August 8
Application Deadline: January 12
Eligibility: Chicago-area current high school seniors; Familiarity with programming languages preferred
The DSI Summer Lab is an intensive eight-week paid summer research program hosted by the University of Chicago's Data Science Institute. During the program, you’ll be paired with mentors from various fields, including computer science, social science, and biomedical research, to work on rigorous, applied, and interdisciplinary data science projects. This immersive experience is designed to help you apply without prior research experience, refine your skills in research methodologies, teamwork, and data science practices. Rooted in a cohort community, the program aims to provide a broad range of students with the conceptual tools needed to engage in high-level research.
2. Veritas AI
Location: Virtual
Cost: Varies depending on program type; Full financial aid is available
Acceptance Rate: Selective
Dates: Multiple 12-15-week cohorts throughout the year, including spring, summer, fall, and winter
Application Deadline: Rolling; Varies by cohort
Eligibility: High school students
Veritas AI, founded by Harvard graduate students, provides high school students with structured learning experiences in artificial intelligence, data science, and machine learning. The AI Scholars program serves as an entry point, guiding you through AI fundamentals in a 10-session boot camp while letting you apply concepts to real-world projects. Programs are designed to be flexible and virtual, accommodating students worldwide. With its tiered structure, Veritas AI allows you to start at an introductory level and advance toward independent research with professional mentorship.
3. Carnegie Mellon University: Statistics & Data Science Camp
Location: Carnegie Mellon University, Pittsburgh, PA
Cost/Stipend: None
Acceptance Rate/Cohort Size: Not specified
Dates: June 23 – June 27
Application Deadline: March 28
Eligibility: High school students in Pittsburgh
The Statistics & Data Science Camp at Carnegie Mellon University is a free, one-week summer program designed to introduce local high school students to the fundamentals of statistics and data science. Each day combines lectures, computer labs, and hands-on demonstrations using the programming language. Topics include data visualization, modeling with regression, and text analysis. You’ll also get to participate in a field trip to Duolingo, gaining insight into how data science is applied in industry. By the end of the program, you’ll understand the basics of how data is collected, analyzed, and used to solve real-world problems. The camp also provides exposure to career pathways in statistics and data science and includes a tour of Carnegie Mellon’s campus.
4. Lumire Research Scholar Program
Location: Remote
Cost: Varies as per different programs; Financial aid is available
Acceptance Rate: Highly selective
Dates: Multiple cohorts year-round
Application Deadline: Varying deadlines based on cohort
Eligibility: High school students with a GPA of at least 3.3 on a 4.0 scale
The Lumiere Research Scholar Program offers motivated high school students the chance to dive into independent research under the guidance of Ph.D. mentors. The program runs in multiple cohorts throughout the year, with flexible durations ranging from 12 weeks to one year. You’ll work one-on-one with a mentor on a self-chosen topic, gaining experience in academic research methods and producing a polished research paper by the end of the program. Areas of study span a wide range, including data science, computer science, economics, psychology, engineering, chemistry, and international relations. Beyond subject knowledge, you’ll develop essential skills in critical thinking, writing, and research methodology. By the conclusion of the program, you’ll have completed a substantial research project, similar to what you’d experience at the university level.
5. NLM Data Science and Informatics (DSI) Scholars Program
Location: NIH Campus, Bethesda, MD
Stipend: Paid
Acceptance Rate: Highly selective
Dates: 8-12 weeks starting June (flexible dates)
Application Deadline: November 18 – February 19
Eligibility: Enrolled in high school at least half-time as a senior or be accepted into an accredited program for the upcoming fall; Must be at least 18 years old by June 1; U.S. citizens or permanent residents; Have a cumulative GPA of 3.2 or higher on a 4.0 scale; Have completed coursework in computer science, data science, informatics, mathematics, or related fields
The NLM Data Science and Informatics (DSI) Scholars Program is a full-time summer internship for high school students, running 8 to 12 weeks at the National Library of Medicine. Designed for those curious about how data science supports health and biomedical research, the program offers an opportunity to contribute to projects in areas such as biomedical informatics, health data analysis, and computational methods. Participants work closely with mentors while applying skills in machine learning, large-scale data processing, and algorithm development on real biomedical datasets. The program also emphasizes professional growth, with students strengthening their scientific communication through presentations and workshops, and showcasing their work at the NLM and NIH Summer Poster Days.
6. CS Scholars Program
Location: Carnegie Mellon University, Pittsburgh, PA
Cost/Stipend: None
Acceptance Rate: Selective
Dates: June 21 – July 19
Application Deadline: March 1
Eligibility: U.S. 10th-11th graders (16+) from underrepresented backgrounds and low-income families
In the CS Scholars Program (CSS), through college-level courses, group projects, faculty lectures, and hands-on research, you’ll build strong foundations in Python programming, algorithms, and data structures. The program emphasizes algorithmic thinking and problem-solving while also strengthening computational skills through a math readiness course. You’ll collaborate on a final project that applies computer science to real-world challenges, presenting your work to peers and faculty. Beyond academics, you’ll participate in college prep seminars, mentorship, and industry engagement with leading tech companies. Students who excel may be invited back the following summer for CMU’s AI Scholars Program, continuing their pathway in advanced computer science and artificial intelligence.
7. Wharton Data Science Academy
Location: The University of Pennsylvania, Philadelphia, PA
Cost: $9,799; Need-based scholarships available
Acceptance Rate/Cohort Size: Highly selective; 75 students
Dates: July 13 – August 2
Application Deadline: January 29 (priority); April 2 (final)
Eligibility: International and U.S. 10th-11th graders with a minimum GPA of 3.3; Must have a strong background in math and coding
The Wharton Data Science Academy provides high school students with a great experience in the field of data science, emphasizing how it is motivated by real-world problems. The program equips you with essential techniques like data visualization and data wrangling while exposing you to modern machine learning methodologies that are the building blocks of today's AI field. As a participant, you will develop working proficiency with the R language, a tool widely used by professional data scientists. You’ll also work in teams to advance your skills with real-world data and complete a final project, which you’ll present to your peers.
8. Syracuse University Summer College Program: Data Visualization and Analysis
Location: Syracuse University, Syracuse, NY
Cost: Residential: $2,395; Commuter: $1,908; Scholarships available
Acceptance Rate: Highly selective
Dates: July 6 – July 11
Application Deadline: May 1 (based on previous years)
Eligibility: Rising high school sophomores, juniors, or seniors
This hands-on course is designed to teach you how to transform raw data into useful, visual information. The curriculum covers the fundamentals of data, including quality assessment and cleaning, and explores design principles for dashboards and charts. You'll start by using Microsoft Excel and then progress to a more sophisticated tool, Tableau, to create data visualizations. The program also focuses on teaching you how to present data to make informed decisions and is suitable for those with no prior coding or programming knowledge.
9. Quinnipiac University’s Pre-College Summer Programs: Data Sciences Lab
Location: Quinnipiac University, Hamden, CT
Cost: Residential: $3,360; Commuter: $2,400; Limited financial aid available
Cohort Size: 30 participants
Dates: July 7 – July 18
Application Deadline: Not specified
Eligibility: Current high school students (ages 15-18)
The Data Sciences Lab is a two-week pre-college program designed for you to explore Big Data concepts and learn how data science influences critical areas like healthcare, business, and public policy. Through engaging lessons, group discussions, and hands-on projects, you’ll analyze real datasets, uncover patterns, and practice solving real-world challenges. The curriculum combines theory with practical application, guided by Quinnipiac faculty in small class settings. Beyond academics, the program includes social activities and excursions for residential students, creating a well-rounded summer learning experience.
10. NYU’s Machine Learning
Location: NYU Tandon School of Engineering, Brooklyn, NY
Cost: Tuition: $3,050 (+additional costs)
Acceptance Rate: Highly selective
Dates: Session 1: June 16 – 27; Session 2: July 7 – 18; Session 3: July 28 – August 8
Application Deadline: May 15; Rolling
Eligibility: Current high school freshmen to graduating seniors who have completed Algebra 2 (or equivalent) and have some programming experience
NYU’s Machine Learning program introduces you to computer science, data analysis, mathematical techniques, and logic, all of which are the basis of machine learning (ML) and artificial intelligence (AI). Through a focus on engineering problem-solving, you’ll learn core ML principles, including model development through cross-validation, linear regressions, and neural networks. You'll gain an understanding of how to apply logic and mathematics to "teach" a computer to perform specific tasks and to continuously improve. You will work on daily assignments and weekly projects designed to give you a solid foundation in AI and ML and the skills to formulate and solve machine learning problems. The course also covers the fundamental knowledge behind video and image recognition, voice controls, autonomous vehicles, and medical technologies.
11. Columbia University’s Pre-College Programs: Data Science and Machine Learning 1
Location: Columbia University, New York, NY
Cost: Varies by format; Financial aid available
Acceptance Rate: Highly selective
Dates: Multiple sessions
Application Deadline: Varies by format
Eligibility: Domestic and international high school students (15+)
This Columbia pre-college course introduces you to the fundamentals of data science and machine learning, emphasizing real-world applications. As a participant, you’ll get hands-on practice coding in Python and working with basic machine learning algorithms, even as a beginner. Instructors guide you through exploring how data is used across industries and the ethical considerations that come with it. This means you’ll also work on analyzing datasets and presenting findings clearly and responsibly. By the end, you’ll have built a strong foundation to continue into more advanced study, including Columbia’s Data Science and Machine Learning II. The program is structured for high school students just beginning their journey in this field, offering both in-person and online sections to fit different schedules.
12. UCLA Summer Sessions: Computer Science Summer Institute – Intermediate Track
Location: UCLA, Los Angeles, CA
Cost: $3,186; Scholarships offered
Acceptance Rate: Competitive
Dates: June 23 – July 11
Application Deadline: June 13
Eligibility: Students in 10th & 12th grade
This is a three-week program designed for those who want to deepen their skills in data science and machine learning. The curriculum combines theoretical instruction with hands-on projects, guiding you through the data science lifecycle, including data cleaning, feature engineering, model selection, and prediction methods. You’ll analyze real-world datasets in areas such as health, economics, geography, and social networks while exploring machine learning and statistical modeling techniques. The program is taught by UCLA faculty and includes lab tours and guest lectures from leading researchers. You will also receive college credit (4 units) upon completion and presentation of final projects.
13. Analytics Academy Summer Pre-College Program
Location: Bentley University, Waltham, Massachusetts
Cost: Commuter: $2,250; Residential: $3,180; Limited need-based scholarships available
Acceptance Rate/Cohort Size: Not specified
Dates: Multiple 5-day sessions
Application Deadline: Varying deadlines; Rolling
Eligibility: Rising high school juniors and seniors
Bentley University’s Analytics Academy is a week-long pre-college program designed to introduce high school juniors and seniors to the fundamentals of data science and analytics. Across five days, you’ll attend sessions that cover topics such as data types, visualization, correlation, data ethics, and storytelling with data. The program provides hands-on experience with Tableau, allowing you to practice creating both basic and advanced visualizations. You’ll also explore real-world applications of analytics through a project, which you’ll present to peers and parents at the program’s conclusion. Beyond academics, the residential format includes community activities and even a field trip to Boston, creating a balanced mix of learning and campus life.
14. UCLA Summer Sessions: Python for Economics and Finance Summer Institute
Location: Virtual
Cost: $2,611; Scholarships offered
Acceptance Rate: Competitive
Dates: July 14 – August 1
Application Deadline: June 13; Rolling basis
Eligibility: Students in grades 9-12 (15+)
The Python for Economics and Finance Summer Institute introduces high school students to the use of Python for data science, economic modeling, and financial analysis. Over three weeks, you’ll learn the foundations of Python programming and how to apply it to real-world datasets in economics and finance. The program emphasizes hands-on work, allowing you to explore economic and financial questions while developing analytical and critical thinking skills. Instruction is led by UCLA Economics faculty, and coursework blends coding exercises, lectures, and project-based applications.
15. BWSI Medlytics
Location: Virtual
Cost: Varies based on family income
Acceptance Rate: Competitive
Dates: July 7 – August 3
Application Deadline: March 31
Eligibility: U.S. 9th-11th graders
Medlytics is a program that introduces high school students to the cutting-edge intersection of data science, machine learning, and medicine. The program begins with an online prerequisite course that builds foundations in probability, statistics, Python coding, and introductory machine learning. If you complete this online portion, you might also be selected for the four-week on-campus program at MIT, where you will work with clinicians and data scientists on real-world medical data challenges. Projects cover areas such as physiological signal analysis, deep learning for medical imaging, and time-series data processing. The program is highly hands-on, providing mentorship from Boston-area researchers and exposure to both the technical and ethical challenges of applying AI in healthcare.
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