Reproducible report
Publish a full analysis in Quarto or R Markdown on an open dataset, from code to final chart.
All pathsDiscover Coursera PlusAfter step 1 After step 2 After step 3
Data & AI · 03Intermediate
R Data Scientist
Future statisticians or applied researchers working in R.
The full R analysis pipeline, from import to reproducible publishing, then modern regression, GLMs and Bayesian inference.
514hours of coursework
52weeks at 10 h
3steps
18courses
3universities
Target skills
Statistical AnalysisData ScienceStatistical InferenceR ProgrammingModel EvaluationStatistical Hypothesis TestingPredictive ModelingMachine LearningRegression AnalysisStatistical MethodsStatisticsData Analysis
Skill labels as listed on Coursera.
Target jobs
- R data scientist
- Junior biostatistician
- Quantitative research officer
Progression
- 1Johns Hopkins UniversityBeginnerR, RStudio, GitHub, R Markdown, knitr, Shiny, Leaflet
Stated prerequisites: Some programming experience (any language); mathematics up to algebra
Show the 10 courses
Course Level Length Rating (reviews) The Data Scientist's Toolbox — 18 h 4.6 (34,111) R Programming Intermediate 58 h 4.5 (22,379) Getting and Cleaning Data — 20 h 4.5 (8,081) Exploratory Data Analysis — 56 h 4.7 (6,092) Reproducible Research — 8 h 4.6 (4,188) Statistical Inference — 55 h 4.2 (4,456) Regression Models — 54 h 4.4 (3,377) Practical Machine Learning — 8 h 4.5 (3,269) Developing Data Products — 10 h 4.6 (2,266) Data Science Capstone — 6 h 4.5 (1,242) - 2University of Colorado BoulderIntermediateR, Jupyter Notebooksacademic credit
Stated prerequisites: Calculus, basic linear algebra and probability theory
Show the 3 courses
Course Level Length Rating (reviews) Modern Regression Analysis in R Intermediate 45 h 4.3 (40) ANOVA and Experimental Design Intermediate 40 h 4.0 (23) Generalized Linear Models and Nonparametric Regression Intermediate 42 h 4.2 (26) - 3University of California, Santa CruzIntermediateR, Microsoft Excel
Show the 5 courses
Course Level Length Rating (reviews) Bayesian Statistics: From Concept to Data Analysis Intermediate 11 h 4.6 (3,233) Bayesian Statistics: Techniques and Models Intermediate 30 h 4.8 (498) Bayesian Statistics: Mixture Models Intermediate 22 h 4.5 (63) Bayesian Statistics: Time Series Analysis Intermediate 19 h 4.3 (18) Bayesian Statistics: Capstone Project Advanced 12 h 4.5 (10)
With Coursera Plus
This path takes 514 hours, about 12 months at 10 hours a week. A Coursera Plus subscription gives access to most of its courses during that time.
Projects to build
Count model
Model accident or case counts with a Poisson GLM, then check for overdispersion.
Bayesian comparison
Compare two treatments with a Bayesian model and test how sensitive the result is to the priors.
Free textbooks
R for Data Science, 2nd ed.H. Wickham, M. Çetinkaya-Rundel, G. GrolemundFree, CC BY-NC-ND 3.0
OpenIntro StatisticsD. Diez, M. Çetinkaya-Rundel, C. BarrFree PDF
Bayesian Data Analysis, 3rd ed.A. Gelman et al.Free PDF, non-commercial use