A professional credential issued by r-statistics.co and earned the hard way: you complete a roadmap track and pass its graded checks, each one graded by running your R and checking what it produces. A line on a resume a hiring manager can click, check, and trust.
Every r-statistics.co credential is earned, not awarded. To hold one you complete a roadmap track: at least 80% of the graded checks across its lessons, each one passed by writing real R that the grader runs and checks. It either works, or it does not.
That is what gives the credential its weight. It attests to skill shown across a whole track of graded exercises, and every credential carries a public verification page, so a recruiter or hiring manager can confirm it in a single click. It is the receipt for work already done.
One path, two steps, and the numbers are the real ones. Take the Data Analyst track: 44 lessons carrying 180 graded checks, and an 80% bar to claim the certificate.
Each certificate is one roadmap track. Pass at least 80% of the graded checks across its lessons, at your own pace. Checks you passed earlier, before you decided to go for the certificate, count toward the bar.
Reach the bar and claim it, from your account or right in the lesson that gets you there. Your credential mints with a unique ID like RST-2026-A7K3F9, a permanent public verification page, and an Open Badges 3.0 record you can add to LinkedIn in one click.
Each certificate is one roadmap track, from the base every R user needs, through the Data Analyst core, to the four specializations. Each states plainly what holding it proves you can do. Certified R Fundamentals is free to earn; the Data Analyst and specialization certificates come with Pro.
You can read and write everyday base R without reaching for a search bar: data types and vectors, data frames and lists, control flow, your own functions, and errors you can actually debug. The floor everything else here stands on.
Syntax and vectors, lists and data frames, subsetting, functions, importing real data, strings and dates, iteration with purrr, defensive code, a reproducible workflow.
You can take a raw file to a clear, defensible analysis: tidy and join it, explore it, chart it with ggplot2, and report it in tables and dashboards people can act on. The shared core every specialization builds on.
dplyr, tidyr, joins and reshaping, exploratory analysis, ggplot2, data.table, gt tables, interactive dashboards, Quarto reporting.
You can carry a problem from raw data to an evaluated model: build with tidymodels, reach for trees and boosting when they fit, engineer features without leakage, and resample honestly so you never fool yourself about accuracy.
The ML workflow, regression and classification, trees and gradient boosting, tidymodels, feature engineering, tuning, calibration, clustering and PCA, interpretability.
You can forecast a series and say how far to trust it: decompose it, fit ETS, ARIMA and state space models, add drivers and hierarchy, and backtest honestly before anyone acts on the numbers.
Decomposition, ETS and ARIMA, dynamic regression, state space models, volatility, multivariate and hierarchical forecasting, ML and deep forecasting.
You can choose the right statistical method and defend it: estimation and inference, regression and GLMs, mixed models, Bayesian analysis and causal inference, reported so it survives review.
Estimation and the bootstrap, test selection, ANOVA, regression strategies, GLMs, mixed-effects models, Bayesian analysis, causal inference, survival analysis.
Lessons are being published now. This certificate opens when the track is complete.
You can write R that other people depend on: functional and object-oriented code, fast hot paths, tested and documented packages, and apps and APIs that run in production.
Functional and OO programming, environments, performance and Rcpp, packages, testing and CI, Shiny, databases and deployment.
Lessons are being published now. This certificate opens when the track is complete.
A credential is only useful if other people can act on it. Yours lives at a public URL anyone can open to confirm it, no account, no email to you, no waiting, and goes onto your LinkedIn profile as a real certification in one click.
Every credential is issued as Open Badges 3.0, the 1EdTech standard for verifiable credentials. It names r-statistics.co as the issuer, carries the holder's score, and lives at a permanent public page. That is the difference between something a recruiter can trust and a JPEG anyone could fake.
A credential is only worth holding if it could have told you no.on why every exercise is code-graded, and can tell you no
Paste any RST ID below to check the holder, track and score for yourself. The card shows what a valid result looks like, using the sample certificate at the top of this page.
Anyone can check a credential without contacting us. The verification page is live and reflects the score and issue date, so it says what the holder demonstrated, and when.
Every tutorial and exercise hub on this site is free. So is the New to R track and its certificate, forever. The Data Analyst and specialization certificates, the ones hiring managers weight most, are part of Pro: Single Track covers Data Analyst plus your chosen specialization, All-Access covers every track. That is where the credential becomes a paid, professional signal, and where Pro earns its keep.
It depends on the track. Certified R Fundamentals is free to earn, with the same public verification page and Open Badge as any other. The Data Analyst and specialization certificates come with Pro: Single Track covers Data Analyst plus your chosen specialization, All-Access covers every track. There is never a separate proctoring fee or exam voucher.
New to R is free so anyone can see the credential is real and earn one at no cost. The career-track credentials, the ones hiring managers care most about, sit inside Pro. That keeps the highest-value signal behind real commitment, which is part of what makes it worth holding.
Pro opens every section of the Data Analyst track and the four specializations, and with them their certificates. The tutorials, the exercise hubs, the New to R track and its certificate stay free.
It is code, not multiple choice. You write real R, and the grader runs it and checks the output against the expected result. There is no option to pick from a list, so the result reflects skill rather than recognition.
You need at least 80% of the graded checks across a track's published lessons before you can claim the certificate. Checks you passed earlier count toward that 80%. Researcher and R Developer certificates open once those tracks are fully published.
Each credential gets a unique ID like RST-2026-A7K3F9 and a public page anyone can load to confirm the holder, track, score and issue date. It is also issued as Open Badges 3.0 JSON naming r-statistics.co as the issuer, and adds to LinkedIn in one click.
Yes. In rare cases of an integrity violation, a credential can be revoked, and its public page then shows that status. That possibility is part of why the credential is worth holding in the first place.
Pick a track, solve the work, and put your name on something that means it.
See the credentials