15 Data Analytics Programs for High School Students
Data drives decisions in healthcare, business, technology, and public policy, and learning how to analyze it early can reshape how you think about problems. That’s why data analytics programs for high school students have become a practical pathway for teens who want real technical exposure. Instead of studying math or coding separately, you work with real datasets, build models, design visualizations, and present findings in research or classroom settings. Many programs are hosted by universities and national research institutions, giving you insight into how data is used in labs and industry.
What are the benefits of a data analytics program?
Data analytics programs allow you to apply statistical and computational methods to study patterns in data. You may learn techniques such as data cleaning, regression and classification modeling, dashboard design, and machine learning methods used in analysis. Some programs conclude with research papers or presentations that require you to explain your methods and findings, while others emphasize business analytics concepts such as KPIs, A/B testing, and clustering.
To help with your search, below is our list of 15 data analytics programs for high school students.
If you’re looking for free online programs, check out our blog here.
1. University of Chicago’s DSI Summer Lab
Location: John Crerar Library at the University of Chicago, Hyde Park campus, IL
Cost/Stipend: No cost; $5,600 stipend
Acceptance rate/cohort Size: Not specified
Dates: June 15 – August 7
Application deadline: January 12
Eligibility: Current high school seniors starting college in the fall and residing in Chicago; Applicants familiar with at least 1 programming language are preferred
The Data Science Institute’s DSI Summer Lab is an eight-week paid research experience where you work directly in an active lab. Participants are paired with mentors across fields such as computer science, public policy, biomedical research, climate and energy policy, and materials science. You contribute to applied data science projects while building skills in research design, data analysis, and collaborative problem-solving. Students also practice communicating findings, culminating in a recorded research presentation delivered at a symposium. Weekly speaker events introduce you to researchers discussing current data-driven challenges and career paths, while professional development workshops and community programming round out the summer experience.
2. Veritas AI Programs
Location: Remote
Cost: Varies by program; need-based financial aid is available for AI Scholars
Acceptance rate/cohort size: Highly selective
Dates: Multiple 12- to 15-week cohorts throughout the year, including in summer
Application deadline: Rolling. Spring (January), Summer (May), Fall (September), and Winter (November). You can apply to the program here.
Eligibility: High school students; AI Fellowship applicants must have either completed the AI Scholars program or have experience with AI concepts/Python
Veritas AI offers mentor-led AI programs in a fully online format designed for high school students. For those new to the field, the AI Scholars track spans ten sessions and introduces machine learning, neural networks, and core data science concepts through guided group projects. You work in small cohorts and receive feedback from mentors affiliated with universities such as Harvard, MIT, and Stanford. If you have prior experience, the AI Fellowship centers on an individual research project completed one-on-one with a mentor, with emphasis on experimental design, model development, and technical writing. The advanced track may include guidance on preparing research for submission to high school journals. You can also check out some examples of past projects here and read about a student’s experience in the program here.
3. NLM Data Science and Informatics (DSI) Scholars Program
Location: NIH Campus, Bethesda, MD
Cost/Stipend: None
Acceptance rate/cohort Size: Not specified
Dates: 8 – 12 weeks starting June (flexible)
Application deadline: February 18 (rolling)
Eligibility: Must be at least 18 years of age by June 1, a U.S. citizen or permanent resident, accepted into an accredited program for the upcoming fall, have a cumulative GPA of 3.2+ on a 4.0 scale, and have completed coursework in computer science, data science, informatics, mathematics, or related fields
This data analytics program for high school students is a full-time summer internship focused on computational health and biomedical data science. As a scholar, you work alongside researchers on projects involving biomedical informatics, health data analysis, machine learning, and large-scale data processing. You train closely with a mentor while strengthening skills in algorithm development and analytical reasoning using real biomedical datasets. Professional development is built into the schedule through seminars and workshops on scientific communication. Your work culminates in presentations at both NLM’s Summer Poster Day and the broader NIH Summer Poster Day.
4. Lumiere Research Scholar Program
Location: Virtual
Cost: Varies; financial assistance offered
Acceptance rate/cohort size: Highly selective
Dates: Multiple sessions of varying lengths (12 weeks – 1 year) available, including summer cohorts
Application deadline: Varies by cohort/multiple cohorts run each year, including in the summer
Eligibility: High school students; accepted students typically have an unweighted GPA of 3.3 out of 4.0
The Lumiere Research Scholar Program is a 12-week remote experience that pairs you with a PhD-level mentor to conduct original research in data analytics or related quantitative fields. After selecting a topic, you develop a research question, complete a literature review, and design a methodology grounded in statistical or computational analysis. Regular mentor meetings guide you through refining hypotheses, interpreting findings, and strengthening analytical rigor. Workshops supplement this work by covering research methods and academic writing. Over the course of the term, your project evolves into a full-length research paper. You can find more details about the program application and available formats here.
5. Carnegie Mellon University (CMU) Pre-College: CS Scholars Program
Location: Carnegie Mellon University campus, Pittsburgh, PA
Cost/Stipend: None
Acceptance rate/cohort Size: Not specified
Dates: June 20 – July 18
Application deadline: February 1
Eligibility: High school sophomores who will be 16 years old by the program start date and are U.S. citizens, permanent residents, or DACA recipients
The CS Scholars Program is a four-week residential experience for high schoolers focused on core computer science foundations. During this data analytics program for high school students, you study Python programming, algorithms, and data structures while strengthening mathematical reasoning for computational work. The coursework is paired with collaborative, project-based learning that culminates in a final presentation applying computing to real-world challenges. Faculty lectures and labs emphasize algorithmic thinking, and weekly college-preparation seminars address admissions, financial aid, and student life. Scholars also engage with industry professionals to understand how computing translates beyond the classroom. Students who demonstrate strong performance may be invited to return the following summer for CMU’s AI Scholars program.
6. Analytics Academy Summer Pre-College Program
Location: Bentley University, Waltham, MA
Cost: Commuter: $2,450 | Residential: $3,380
Acceptance rate/cohort size: Not specified
Dates: Multiple 5-day sessions, residential and commuter options available
Application deadline: June 1 (rolling)
Eligibility: Rising high school juniors and seniors
Bentley University’s Analytics Academy is a five-day residential pre-college program introducing high school juniors and seniors to foundational data analytics concepts. Across the week, you examine data types, correlation, visualization techniques, and principles of data ethics and storytelling. This data analytics program for high school students covers hands-on work with Tableau, where you build both introductory and more advanced visualizations. Sessions address how to clean datasets and interpret patterns before concluding. The academic portion culminates in a capstone project presented at the end of the program.
7. UPenn’s Wharton Data Science Academy
Location: The Wharton School at the University of Pennsylvania, Philadelphia, PA
Cost: $10,599 + $100 application fee; need-based financial aid available
Acceptance rate/cohort size: Not specified
Dates: June 21 – July 11 | July 12 – August 1
Application deadline: March 18
Eligibility: Students in grades 10 – 11 with strong math and coding skills, an interest in data analytics, and preferably some knowledge of statistics
At the University of Pennsylvania’s Wharton Data Science Academy, the curriculum mirrors upper-level undergraduate coursework. You begin with data wrangling, visualization, probability, and statistics, including hypothesis testing and confidence intervals. The experience then advances into regression modeling, classification techniques, and elements of modern machine learning. R serves as the primary programming language, with Python used selectively for topics such as neural networks and large language models. Daily labs and guided case studies ensure you apply concepts to real datasets. The experience culminates in a team-based capstone project presented during a final showcase.
8. Syracuse University Summer College Program: Data Visualization and Analysis
Location: Syracuse University, Syracuse, NY
Cost: Residential: $2,795 | Commuter: $2,309
Acceptance rate/cohort size: Not specified
Dates: July 19 – 24
Application deadline: Not specified
Eligibility: Rising high school sophomores, juniors, or seniors
Syracuse University’s Data Visualization and Analysis course centers on transforming raw datasets into structured, decision-ready visual information. You begin by learning how to assess data quality, clean incomplete datasets, and conduct basic statistical analysis. Microsoft Excel is used first to develop core analytical skills, and then Tableau is used for dashboard design and advanced visualization. This data analytics program for high school students covers principles of chart selection, layout design, and data storytelling. Throughout the course, you practice presenting findings clearly to hypothetical stakeholders. Students who complete the program receive a Certificate of Completion and may request a noncredit Syracuse University transcript.
9. NYU’s Machine Learning Program
Location: NYU Tandon School of Engineering, Brooklyn, NY
Cost: $3,180 tuition + additional optional costs
Acceptance rate/cohort size: Not specified
Dates: Session 1: June 15 – 27 | Session 2: July 6 – 17 | Session 3: July 20 – 31
Application deadline: May 15
Eligibility: High school students in grades 9–11 who have some programming experience and have completed Algebra 2 | Applicants typically have a minimum 3.0 GPA
NYU Tandon’s two-week Machine Learning program introduces high school students to the mathematical and computational foundations underlying artificial intelligence. You study data analysis techniques alongside topics such as linear regression, cross-validation, and neural networks. Daily assignments and weekly projects reinforce how models are developed, tested, and improved. The curriculum connects theory to applications, including image recognition, speech processing, and medical diagnostics. Engineering problem-solving principles guide how you frame and evaluate predictive models.
10. Quinnipiac University’s Pre-College Summer Programs: Data Sciences Lab
Location: Quinnipiac University, Hamden, CT
Cost: Residential: $3,600 | Commuter: $2,600
Acceptance rate/cohort size: 30 participants
Dates: July 6 – 17
Application deadline: June 1
Eligibility: Current high school students ages 15–18
Quinnipiac University’s two-week data analytics program for high school students introduces participants to Big Data theory and applied analytics. Participants examine how data scientists use mathematics, statistics, and programming concepts to detect patterns and inform decisions across business, healthcare, and public policy. The coursework combines lectures with hands-on dataset analysis conducted in small classes. You also explore how data supports product development, policy decisions, and artificial intelligence models. Residential students also take part in organized weekend excursions and community activities.
11. Carnegie Mellon University: Statistics & Data Science Camp
Location: Carnegie Mellon University, Pittsburgh, PA
Stipend: Paid
Acceptance rate/cohort size: Not specified
Dates: June 22 – 26
Application deadline: March 15
Eligibility: Pittsburgh high school students
Carnegie Mellon University’s Statistics & Data Science Camp is a free, one-week introduction to statistical reasoning and data analysis for high school students. Each day blends foundational lectures with computer labs in R. Topics include data visualization, regression modeling, and text analysis, with students also taking a field trip to Duolingo to observe data science in action within a tech company's environment. The camp emphasizes how vast amounts of digital data can be compiled and analyzed to answer real-world questions.
12. USC Pre-College: Analytics – The Power of Data for Businesses
Location: University of Southern California, Los Angeles, CA
Cost: Residential: $11,570 | Commuter: $8,130
Acceptance rate/cohort size: Not specified
Dates: June 22 – July 17
Application deadline: International: March 13 | Domestic: May 8
Eligibility: High school students with proficiency in high school-level math; View additional criteria
USC’s “Analytics: The Power of Data for Businesses” course examines how organizations use data to guide strategic decisions. You practice cleaning datasets, building visualizations, and defining key performance indicators that measure outcomes. The curriculum introduces classification, clustering, predictive modeling, experimental design, and A/B testing. Python is integrated to help you implement and evaluate analytical models. Case-based modules connect quantitative techniques to marketing, finance, operations, and economics. You also learn about data ethics and the limits of algorithmic evidence
13. Columbia University’s Pre-College Programs: Data Science and Machine Learning 1
Location: Columbia University, New York, NY
Cost: Varies by session and format; financial aid available
Acceptance rate/cohort size: Not specified
Dates: Multiple sessions available
Application deadline: Varies by session
Eligibility: Domestic and international high school students aged 15+
Columbia University’s Data Science and Machine Learning I course introduces high school students to analytical thinking by exposing them to Python and foundational algorithms. You study how datasets are analyzed across industries while learning core machine learning concepts at an introductory level. The course focuses on understanding how data-driven models impact real-world systems. It also includes coding exercises and explores ethical issues related to data use and presentation. The program equips students for more advanced quantitative studies, including a second-level course.
14. Tufts University Pre-College Programs: Engineering with Artificial Intelligence
Location: Tufts University, Medford, MA
Cost: Commuter: $4,425 | Residential: $5,950 | Limited need-based scholarships available
Acceptance rate/cohort size: Not specified
Dates: Session 1: July 5 – 17 | Session 2: July 19 – 31
Application deadline: May 1
Eligibility: Students entering grades 10-12 or recent graduates
Tufts University’s Engineering with Artificial Intelligence program spans three weeks and introduces students to the technical and societal dimensions of AI and machine learning. Classroom sessions provide historical context and mathematical foundations behind algorithm design and model training. In labs, you examine how data analysis methods support larger intelligent systems while discussing ethical responsibilities and societal impacts of automated decision-making tools. Guest speakers from academia and industry showcase current AI applications. Participants have the opportunity to design and develop their own AI-based solution to a specified problem.
15. Northeastern University’s Young Scholars Program (YSP)
Location: Northeastern University, Boston, MA
Cost/Stipend: None
Acceptance rate/cohort size: Not specified
Dates: June 22 – July 3
Application deadline: March 2
Eligibility: Current high school juniors who are permanent residents of Massachusetts and attend school in the state; more information here
Northeastern University’s Young Scholars Program is a six-week summer research experience placing high school students in university laboratories across engineering, science, and health disciplines. Depending on placement, you may engage in coding, experimental design, and data analysis tied to ongoing faculty research. Weekly seminars introduce engineering fields, cooperative education pathways, and STEM career preparation. Field trips to organizations such as Biogen and the Massachusetts Clean Energy Center provide exposure to applied research environments. Participants also receive college and career counseling during the session. The experience concludes with a formal poster presentation summarizing your research findings.
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