15 Data Analysis Programs for High School Students
If you're thinking about a future in business, finance, economics, or any analytics-driven field, gaining early experience in data analysis can give you a head start.
What are data analysis programs for high school students?
You’ll learn foundational tools like Python, R, SQL, and visualization platforms. You’ll explore machine learning basics, understand how to clean and interpret raw data, and practice communicating insights clearly. This combination of technical and analytical skills is valuable no matter what major you eventually choose. Beyond coursework, many programs also give you access to mentors from universities, research labs, and industry.
Why pursue data analysis programs for high school students?
These experiences can significantly strengthen your college applications because they demonstrate initiative, quantitative ability, and comfort with advanced problem-solving. And if you're building a small business, the skills you gain can help you make smarter decisions. You’ll also get a clearer sense of whether a career in data-driven problem-solving is right for you, something most students only figure out much later.
If you’re also interested in business analytics internships, check here!
With that, here’s a list of 15 data analysis programs for high school students!
15 Data Analysis Programs for High School Students
1. Wharton Data Science Academy
Cost: $10,599; financial aid and scholarships are available
Location: Philadelphia, PA
Program Dates: June 21–July 11, 2026; July 12–August 1
Application Deadline: Priority: January 28; Final: March 18
Eligibility: Students in grades 10–11 with a strong background in math and coding; prior statistics preferred; minimum unweighted 3.3 GPA recommended.
The Wharton Data Science Academy is a selective three-week pre-college program where you work directly with Wharton faculty and teaching assistants on hands-on data analysis, machine learning concepts, and statistical modeling. The capstone project forms the core of the experience where your team selects a real dataset, develops a data-driven solution, and presents the full workflow at the Data Science Live showcase. You also explore text analytics, neural network fundamentals, vectorization, embeddings, and responsible AI practices using selective Python modules in Colab. Notable features include guest workshops, Wharton admissions insights, structured mentorship from undergraduate and graduate TAs, and occasional simulations or site visits tied to data ethics or AI careers.
2. USC Pre-College: Analytics – The Power of Data for Businesses
Cost: Residential: $11,570 total; Commuter: $8,130 total
Location: Los Angeles, CA
Program Dates: June 22–July 17
Application Deadline: International: March 13; Domestic: May 8,
Eligibility: High school students; proficiency in high school–level math required; no calculus needed.
This USC pre-college course introduces you to business analytics through hands-on work with data cleaning, visualization, classification, clustering, and A/B testing. You experiment with algorithms businesses use to predict behavior, identify customer segments, and evaluate evidence, while also learning to build KPIs and dashboards for decision-making. The program integrates Python programming, allowing you to develop classification and clustering models with support from both instructors and LLM-assisted coding. Weekly modules walk you through turning raw data into insights, testing hypotheses, and interpreting patterns across finance, operations, marketing, and economics. Notable features include company visits to organizations like Google and the LA City Hall, plus a business pitch competition, industry guest interactions.
3. Young Founders Lab
Cost: Varies depending on program type. Full financial aid available.
Location: This program is 100% virtual, with live, interactive workshops
Program Dates: Multiple cohorts throughout the year, including summer, fall, winter, and spring
Application Deadline: Varies according to cohort. You can access the application link here!
Eligibility: The program is currently open to all high school students
The Young Founder’s Lab is a start-up boot camp founded and run by Harvard entrepreneurs. In this program, you will work towards building a revenue-generating start-up that addresses a complex problem. You will also have the opportunity to be mentored by established entrepreneurs and professionals from Google, Microsoft, and X. Apart from building the start-up itself, you will also participate in interactive classes on business fundamentals, workshops, skill-building sessions, case studies, and more. The program is an excellent opportunity to delve into the world of business in high school and have a space to explore multiple theoretical as well as practical frameworks that lead to a successful business.
4. Ladder Internship Program
Cost: Varies as per program; financial aid available
Location: Remote! You can work from anywhere in the world.
Application deadline: Deadlines vary depending on the cohort
Program dates: Multiple cohorts throughout the year
Eligibility: Students who can work for 10-20 hours/week, for 8-12 weeks. Open to high school students, undergraduates, and gap year students!
Ladder Internships is a selective start-up internship program for ambitious high school students. Start-ups that offer internships span a variety of industries, including tech/deep tech, AI/ML, health tech, marketing, journalism, consulting, and more. Past founders have included Y Combinator alums, founders who have raised over $ 30 million, and founders who have previously worked at Microsoft, Google, and Facebook. In the program, you work closely with your managers and a Ladder Coach on real-world projects and present your work to the company. You are offered one-on-one training in communication, time management, and other such valuable skills. You will also have the opportunity to attend group training sessions with other interns in your cohort. The virtual internship is usually 8 weeks long.
5. Wolfram High School Summer Research Program
Cost: $5,500
Location: Bentley University, Waltham, MA
Program Dates: June 24–July 11
Application Deadline: Early Decision: January 18; Regular Decision: March 22
Eligibility: Students ages 14–17 (exceptional 13-year-olds considered); strong interest in STEM; no prior CS required; must be under 18 by program end.
This program immerses you in advanced computational thinking, data analysis, and algorithmic modeling using Wolfram Language and Mathematica. You begin with a structured boot camp, then progress into hands-on challenges involving classifiers, simulations, data visualization, NLP, computational art, and interactive web tools. The core experience is the independent research project: you choose a topic, work closely with mentors to build models, analyze patterns, or run simulations that align with your interests. You develop a full computational essay and an interactive research paper, both of which are published at the end of the program. Notable features include deep-dive lectures, optional specialist talks, a minor track (writing, music, art, etc.), a field trip to MIT, and one-on-one Q&A sessions with Stephen Wolfram.
6. Carnegie Mellon Statistics & Data Science Camp for High-School Students
Cost: Free
Location: Carnegie Mellon University, Pittsburgh, PA
Program Dates: June 23–27
Application Deadline: March 28
Eligibility: High school students from Pittsburgh and surrounding school districts; applications from outside the local area are not considered.
This one-week camp introduces you to statistics and data science through a mix of morning lectures and hands-on R computer labs focused on data generation, measurement, similarity, and modeling. You work directly with datasets in R across four lab sessions, learning how to structure data, run basic analyses, build simple linear regression models, and experiment with text analysis and unstructured data. You’ll also explore how data science is used in real products and services during a field trip to Duolingo and tours of Carnegie Mellon. By the end of the week, you gain practical exposure to coding in R, an understanding of how models support decision-making, and a clearer view of careers and academic paths in statistics and data science.
7. The Coding School – National High School Research Program (Data Science Track)
Cost: $3995
Location: Online
Program Dates: 5-week virtual summer research program; this year’s dates are yet to be announced
Application Deadline: Rolling admissions until spots are filled (early application recommended)
Eligibility: Incoming 9th–12th graders and rising college freshmen; open to students of all backgrounds with a strong interest in data science, AI, or quantum computing and access to a computer with Zoom, Google Colab, and RStudio.
In the Data Science track, you spend the first two weeks in intensive technical training, learning data wrangling, analysis, and visualization using tools like R, Google Colab, and standard machine learning workflows. You’ll work closely with a mentor to design and execute an independent research project using real datasets, framing research questions, and interpreting outputs to reach evidence-based conclusions. You’ll practice building plots, training ML models, and structuring end-to-end analyses that could feed directly into a portfolio or science competition. The program also emphasizes research protocol, written and oral presentation skills, and best practices for structuring college-level projects.
8. Data Science Institute Summer Lab – University of Chicago
Cost: Fully funded; paid position with a $5,600 stipend for the 8-week program
Location: University of Chicago, Hyde Park campus, Chicago, IL
Program Dates: June 15 – August 7
Application Deadline: January 12
Eligibility: Chicago-area high school students who can comfortably commute to the Hyde Park campus; must be under 18, authorized to work in the U.S., and able to provide documentation for stipend processing.
As a high school participant in DSI Summer Lab, you work as a full-time (9 a.m.–5 p.m.) research assistant, paired with a data science mentor in areas such as computer science, social science, public policy, climate and energy, materials science, or biomedical research. You’ll be contributing to tasks like cleaning and organizing datasets, writing analysis scripts, running models, and interpreting results in collaboration with your mentor and team. Over eight weeks, you develop practical skills in data pipelines, statistical reasoning, basic machine learning, and research workflow, along with experience using standard programming tools and collaborative practices. The program is intentionally cohort-based, so you also participate in seminars, technical talks, and group events that expose you to different data science applications across campus.
9. NIST Summer High School Intern Program (SHIP)
Cost: Fully funded; participants receive a paid internship stipend (amount varies by lab and year)
Location: NIST campuses in Gaithersburg, MD, or Boulder, CO
Program Dates: Varies by lab; typically 8–10 weeks in summer
Application Deadline: January 26
Eligibility: U.S. citizens only; must be a high school junior or senior at the time of application; must meet lab-specific coursework requirements in areas such as computer science, physics, chemistry, engineering, or math.
As a SHIP intern, you work directly inside a NIST research laboratory paired with federal scientists who specialize in fields such as data mining, machine learning, applied mathematics, software engineering, cryptography, materials simulation, or computational modeling. Your role may involve writing analysis scripts, cleaning and visualizing datasets, building classifiers, developing measurement models, or conducting simulations. You’ll also contribute to federal research outputs through literature reviews, experiment setup, and data interpretation under mentor supervision. Most labs use tools like Python, R, MATLAB, or specialized NIST modeling frameworks, so you gain hands-on experience with domain-specific software. The program also includes cohort events, poster sessions, and exposure to multi-disciplinary federal research teams.
10. Aspiring Scientists Summer Internship Program (ASSIP) – George Mason University
Cost: $1299 tuition for 3 college credits (full tuition waiver available for financial need)
Location: George Mason University, Fairfax, VA (in-person, hybrid, and remote options depending on mentor)
Program Dates: June 18 – August 12
Application Deadline: February 15
Eligibility: High school and undergraduate students; remote interns must be 15+; in-person wet-lab interns must be 16+; no max age as long as the student has not yet graduated from college.
ASSIP offers an intensive 8-week research experience where high school students work directly with Mason faculty and partner institutions on cutting-edge, original research. Projects span computational fields such as data mining, machine learning, cybersecurity, atmospheric modeling, computer simulations, and geospatial data analysis. You’ll receive training in scientific writing, abstract preparation, literature review, poster design, and research communication. Most computational mentors use tools like Python, R, MATLAB, GIS platforms, or domain-specific modeling software, giving you hands-on experience with real research workflows. You’ll complete a full research project, earn three transferable college credits, and showcase your work at a final poster session.
11. NLM Data Science & Informatics (DSI) Scholars Program – National Library of Medicine (NIH)
Cost: Fully funded; paid NIH stipend
Location: National Institutes of Health (NIH), Bethesda, MD
Program Dates: June – August (8–12 weeks; flexible start and end dates)
Application Deadline: February 18
Eligibility: U.S. citizens/permanent residents; high school seniors (enrolled at least half-time), admitted rising college freshmen, and current college students; must be 18+ and have a minimum 3.2 GPA; must have coursework in CS, data science, informatics, math, or related fields.
This program places students on computational biology and health informatics research teams at the National Institutes of Health. You will work full-time on data-driven projects involving biomedical datasets, algorithm development, clinical informatics, machine learning, or computational modeling. You’ll collaborate one-on-one with NIH researchers, gain exposure to high-performance computing environments, and learn how data science is applied to genomics, medical imaging, molecular biology, and public health. You will also build scientific communication skills through weekly seminars, workshops, and required poster presentations at both the NLM Summer Poster Day and the NIH-wide Poster Day.
12. Carnegie Mellon University – CS Scholars Program
Cost: Fully funded (tuition, housing, meals, field trips covered; limited travel aid available)
Location: Carnegie Mellon University, Pittsburgh, PA
Program Dates: June 20 – July 18
Application Deadline: February 1
Eligibility: Rising 11th graders; must be 16+ by June 20; U.S. citizens/permanent residents; documentation of financial need required to apply.
This four-week residential program immerses you in college-level computing, mathematical reasoning, and technical project development. You engage in classroom instruction, hands-on coding challenges, and group problem-solving projects that mirror real-world analytical workflows. You work closely with CMU faculty, staff, and researchers, attend industry guest lectures, and explore data-driven applications of computer science through project-based learning. The program emphasizes technical skill-building, collaborative computation, and a final symposium where you present your work, mirroring the analytical communication expected in data, CS, or AI fields. You also participate in structured college-prep workshops covering admissions, financial aid, and academic pathways, with the option to be invited back for the advanced AI Scholars program the following summer.
13. University of the Pacific – Data Science Boot Camp
Cost: $3,800 (includes tuition, housing, meals, and all activities)
Location: University of the Pacific, Stockton, CA
Program Dates: June 16–June 26
Application Deadline: Registration-based; seats reserved on a first-come basis
Eligibility: High school students (grades not specified)
This 10-day residential boot camp introduces high school students to the foundations of data science through Python, machine learning principles, predictive modeling, and data visualization. You learn to read and transform data across formats, experiment with real datasets, and build basic ML systems that detect patterns and generate predictions. The curriculum covers exploratory data analysis, supervised learning, and visualization techniques using hands-on labs aligned with introductory college-level coursework. The program is led by faculty in data science and computational mathematics, offering direct mentorship from researchers working at the intersection of computer science, biology, and statistics.
14. Digital Scholars Program – Discovery Partners Institute (Chicago, IL)
Location: Chicago, IL
Cost: Free
Program Dates: June 23 – August 1
Application Deadline: May 2
Eligibility: Rising 11th and 12th graders, and first-year college students at City Colleges of Chicago or Illinois institutions. Priority is given to students from Chicago Public Schools and Chicago-area districts.
The Digital Scholars Program is a six-week, in-person summer experience designed to help students build strong technical foundations in areas like data analysis, computing, and app development. You can choose from tracks such as Data Science Discovery, Swift programming, electrical and computer engineering, and iOS app design, gaining structured exposure to analytical tools, dataset exploration, and applied coding. The program also includes daily industry talks with Chicago-area technologists and entrepreneurs, giving you an understanding of how technical fields operate in practice. Weekly workshops on AI, machine learning, entrepreneurship, and data science help you build breadth beyond your chosen track.
15. Data Science and Machine Learning I – Columbia University Pre-College
Cost: Varies for online and in-person programs
Location: New York, NY (In-person & online options)
Program Dates: Varies per program
Application Deadline: Early Registration: February 2; General Deadline (Residential): March 2; General Deadline (Commuter/Online): April 2
Eligibility: High school students; course intended for students with no prior coding/programming experience.
This introductory course gives you a structured foundation in both data science and machine learning through hands-on exposure to Python, algorithm basics, and real-world dataset applications. You begin by mapping the data science landscape and examining use cases across industries, before moving into coding sessions where you practice data manipulation and exploratory analysis. You also learn benchmark machine learning techniques and experiment with applying simple algorithms to real datasets in a controlled setting. As part of the course, you’ll analyze structured data, interpret outputs, and present findings with an emphasis on ethical use of data. By the end of the session, you will understand core ML concepts, gain coding confidence, and be prepared for more advanced coursework.
Image Source - University of Chicago logo