Individuals
Learn employer-valued Python, R/Stan, ML & Shiny—taught through sports so it clicks. Ship portfolio projects.
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Data Science Courses with Built-In Cloud Labs
Learn Python, R, Shiny, Machine Learning, and Bayesian modeling with real sports data—complete with 1-click cloud VMs and portfolio-ready projects.
1,000+ learners • 200+ industry reviewers • Learners from universities & pro teams
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Who Is AthlyticZ For?
State-of-the-art curriculum by top instructors • Built on real sports data • Cloud labs included
Teams & Universities
Cohort training with turnkey cloud labs. License our curriculum at scale or add a Pro Member for guided office hours.
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Tutoring Centers
License modern data curricula + cloud labs to deliver engaging, industry-relevant training with zero setup.
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Explore Our Data Science Courses
Python & Machine Learning
Includes Cloud LabAutograding
FoundationZ, Python MachineZ, model evaluation, feature engineering.
R & Stan (Bayesian Modeling)
Includes Cloud LabPosterior Workflow
Becoming a BayeZian I & II—GLMs, survival, hierarchical models.
Shiny Application Development
Includes Cloud LabDeploy to Prod
ProductioniZing Shiny, CustomiZing Widgets, Mobile StructureZ.
How It Works
1) Enroll
Pick a course or bundle aligned to your goal.
Pick a course or bundle aligned to your goal.
2) Launch Cloud Lab
1-click VM with Python/R/Stan + data preloaded.
1-click VM with Python/R/Stan + data preloaded.
3) Ship Projects
Real sports datasets, autograding/unit tests, portfolio output.
Real sports datasets, autograding/unit tests, portfolio output.
What You’ll Be Able to Do — End-to-End
Graduate with employer-ready skills: production apps, reproducible ML pipelines, Bayesian modeling, testing, deployment, and operations.
Ship production Shiny apps
Auth, role-based access, testing, CI, and containerized deploys to Posit Connect / Shiny Server / cloud.
Fit & interpret Bayesian models
Stan/PyMC workflow: priors, HMC diagnostics, posterior predictive checks, uncertainty communication.
Build robust ML pipelines
Feature engineering → evaluation (scikit-learn/tidymodels) with metrics, cross-validation, and reproducible seeds.
Operationalize models (MLOps)
Versioning, model registry, reproducible builds, monitoring, and scheduled retraining with cloud runners.
Deliver credible data products
Clear visuals, uncertainty bands, and narrative structure tuned for coaches, execs, and stakeholders.
Work fast in cloud labs
One-click VMs with datasets, unit tests, and autograding — everything pre-installed and ready to ship.
Learn from Practitioners
Hands-on instructors from pro teams, top universities, and modern data orgs.
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What learners and partners say
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Sam Denomme
Sports Analytics Professional
“Python MachineZ is one of the most well-structured and thoughtfully delivered introductions to applied ML in sports that I’ve come across.”
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Mitch Henderson, PhD
Senior Data Scientist, NSW Health Pathology
“AthlyticZ teaches relevant, practical skills directly applicable to real-world sports problems—carefully curated and taught by true experts.”
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Bill Geivett, M.Ed.
President @ IMA TEAM • Former MLB Exec
“The course structure is intuitive, the content comprehensive, instructors top-tier, and projects have immediate impact.”
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Brad Smith, PhD
Senior Performance Analyst @ Nebraska
“Hands-on projects connect theory to real-world sports analytics.”
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Brian Burke
Sports Data Scientist, ESPN
“Paul is a master data scientist and R programmer. His instruction was essential to my most recent major project.”
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Erik Larsson
Former Analyst, Green Bay Packers
“Dr. Sabin’s sports analytics course at Virginia Tech was instrumental in landing my first job.”
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Scott Nestler, PhD
Professor, University of Florida
“Paul explains complex Bayesian concepts clearly—these courses are invaluable.”
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Erika Borelli
Data Scientist
“I’m already applying ProductioniZing Shiny. Fantastic teaching from Veerle!”
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Kyle Evans
Professional Baseball Solutions @ Teamworks
“Re-learned modern coding with baseball-relevant examples at my own pace. Highly recommended.”