Programs · for families
The High School Masterclass: a live session every week in real data science, taught by working practitioners, for high school students.
AI coaching is built into the practice sessions. The coach takes the stakeholder's part, and your student works the problem in whatever medium the question actually calls for.
AI as copilot, not autopilot. Students are taught to direct the machine and defend the output, which is the habit that outlasts whatever tool they end up using.
Shaped like a school year because that is the rhythm you are already planning against. Every phase names the thing that appears on the screen, not the topic it came from.
A student who has never written a line of code opens a notebook in the browser and gets a real answer out of real data in the first session.
Open a dataset nobody has prepared for them and find something in it worth telling you about.
Writes and runs Python. Works with real data rather than classroom exercises. This is the line that separates a student who has taken a coding class from one who has used code to answer a question.
The stretch where it stops being exercises. One sports data project, carried from a question through to a finding, at their own pace.
Explain a result to a room, including what it does not prove.
An independent research project with a written conclusion. Something concrete to name in an essay, an interview, or a supplemental question, with a link attached rather than a claim.
The part that outlasts the school year: a page they can send to anyone, with real work on it and their name at the top.
Send a link to a teacher, a coach, or an admissions reader and have it stand on its own.
A live portfolio URL with two projects on it. The rare thing a high school student can put on an application that a reader can actually open and check.
The same three terms, with the work that exists at the end of each one. These are the artifacts, drawn from models the student writes.
A student picks the sport. The methods underneath are the same, and the sport is what makes a sixteen-year-old finish the project.
A sprint model integrated in the browser: force, a falling top speed, and drag, with 100 meter splits read off the curve.
An illustrative runner, not a real performance. The split pattern is the one a well-run 400 produces.
Located pitches with break tails, plus horizontal against induced vertical break by pitch type.
Velocities and break values are illustrative, in the ranges these pitch types actually live in. No real pitcher, team or game.
Writes and runs Python. Works with real data rather than classroom exercises. This is the line that separates a student who has taken a coding class from one who has used code to answer a question.
Expected points per shot over a half court, with a five-touch possession drawn on top.
Shot volumes and percentages are illustrative. The shape is the real argument: a corner three beats a long two on value, not on vibes.
Open-play xG as a logistic in goal angle and log distance, under a passing network sized by touches.
Positions, touch counts and pass volumes are illustrative. Pitch and penalty-area dimensions are the real ones.
An independent research project with a written conclusion. Something concrete to name in an essay, an interview, or a supplemental question, with a link attached rather than a claim.
Routes drawn at real depths off the line, beside a win probability line across one drive.
The drive and its probabilities are invented. Route depths are the ones these routes are actually run at.
Two-sigma dispersion ellipses from a bivariate normal, the same object as a golfer's shot cone.
Landing-point means, spreads and shares are illustrative. Court and service-box dimensions are the real ones.
A live portfolio URL with two projects on it. The rare thing a high school student can put on an application that a reader can actually open and check.
Someone walks up and wants an answer. Practice runs on a clock, and the review afterwards is about the thinking rather than the answer.
Practice is timed. You get a real task and a clock, not a quiz. The session is recorded, and the review afterwards is about the reasoning you showed rather than whether you reached the expected answer.
Scenarios are written the way the question actually arrivesEach one is on sale on its own, as a recording you buy once, on its own page. The program is the order, the weekly work around them and the capstone at the end.
Async masterclass · 75 min
What Fills the Seats
Greg MatthewsPhD · Director, Center for Data Science and Consulting @ Loyola University Chicago
After this you can fit ridge, lasso and elastic net on the same data, tune them honestly, and pick the one that generalizes.
Course · 66 lessons
PYTHON FROM PUCK DROP
FoundationZ of Data Science
Evan Callaghan
After this you can load a season of data in Python, clean it, and answer a question nobody handed you the answer to.
Technical writing is taught as its own skill: writing up a finding so a reader can follow the reasoning, state what the work shows, and state what it does not. Presenting to a non-technical audience is practiced out loud, with questions afterwards, because a result nobody understood is a result nobody used.
Students work in Python and R, the two languages this field runs on, use version control from early on, and every session is taught live and recorded, so a student who misses one for a game or a meet has not missed the material. The skills are the same foundations the programs are built on, taught at a high school level.
Education savings account programs differ by state and their rules change without notice to vendors. Here is exactly where we stand.
Arizona. We are an approved ClassWallet vendor, which is the platform Arizona's Empowerment Scholarship Account program pays through. We provide an itemized invoice separating live instruction from curriculum, which is the documentation these programs ask for.
Florida is pending. It runs through a different administrator and a different marketplace. We are working through it and it is not live yet. That is the whole of what we can say today.
Whether your account covers it is your program administrator's decision, not ours. Ask them, and we will provide whatever documentation they need.
We describe what your student builds. We do not promise admission, a scholarship, or a job. We provide completion records. We are not a degree-granting or accrediting institution, and we make no claim about admissions, scholarships, or placement.
A short call: what they are interested in, where they are, and whether this is a fit.
Ask about your studentFirst name and email. One message when a session recording, a skill, a cheat sheet or a posting worth your time arrives here, and no other mail. Replies reach a person.