- T Tests & ANOVA
- Multiple Regression
- Categorical and Non-Parametric Analysis
- Factor Analysis
- Structural Equation Modeling

- introduction to Bioconductor in R
- RNA-seq with Bioconductor in R
- differential expressiion analysis with limma in R
- single cell RNA-seq with Bioconductor in R
- ChIP-seq with Bioconductor in R
- Certificate

- data manipulation with dplyr
- joining data with dplyr
- case study: exploratory data analysis in R
- data manipulation with data.table in R
- joining data with data.table in R
- Certificate

- introduction to data visualization with ggplot2
- intermediate data visualization with ggplot2
- visualization best practices in R
- Certificate

- introduction to R
- intermediate R
- introduction to the Tidyverse
- data manipulation with dplyr
- joining data with dplyr
- introduction to data visualization with ggplot2
- intermediate data visualization with ggplot2
- introduction to importing data in R
- intermediate importing data in R
- cleaning data in R
- working with dates and times in R
- introduction to writing functions in R
- exploratory data analysis in R
- case study: exploratory data analysis in R
- correlation and regression in R
- supervised learning in R: classification
- supervised learning in R: regression
- unsupervised learning in R
- cluster analysis in R

- survival analysis in R
- designing and analyzing clinical trials in R

- introduction to importing data in R
- intermediate importing data in R
- cleaning data in R
- working with data in the tidyverse
- Certificate

- interactive maps with leaflet in R
- interactive data visualization with plotly in R
- intermediate interactive data visualization with plotly in R
- visualizing big data with Trelliscope in R
- interactive data visualization with rbokeh
- Certificate

- supervised learning in R: classification
- supervised learning in R: regression
- unsupervised learning in R
- machine learning in the tidyverse
- multiple and logistic regression in R
- cluster analysis in R
- machine learning with caret in R
- tree-based models in R
- support vector machines in R
- advanced dimensionality reduction in R
- fundamentals of Bayesian data analysis in R
- topic modeling in R
- hyperparameter tuning in R
- Bayesian regression modeling with rstanarm
- introduction to Spark with sparklyr in R
- Certificate

- network analysis in R
- predictive analytics using networked data in R
- network analysis in the tidyverse
- case studies: network analysis in R

- foundations of probability in R
- multivariate probability distributions in R
- probability puzzles in R
- mixture models in R
- Certificate

- introduction to the Tidyverse
- project: Dr. Semmelweis and the discovery of handwashing
- data manipulation with dplyr
- writing efficient R code
- working with dates and times in R
- project: drunken datetimes in Ames, Iowa
- string manipulation with stringr in R
- working with web data in R
- introduction to writing functions in R
- project: clustering Bustabit gamling behavior
- introduction to shell
- parallel programming in R
- defensive R programming
- developing R packages
- object-oriented programming with S3 and R6 in R
- Certificate

- building web applications with Shiny in R
- case studies - building web applications with Shiny in R
- building dashboards with shinydashboard
- building dashboards with flexdashboard
- Certificate

- visualizing geospatial data in R
- spatial analysis with sf and raster in R
- spatial statistics in R
- interactive maps with leaflet in R
- Certificate

- foundations of inference
- inference for categorical data in R
- inference for numerical data in R
- inference for linear regression in R
- Certificate

- introduction to data in R
- exploratory data analysis in R
- modeling with data in the tidyverse
- correlation and regression in R
- multiple and logistic regression in R
- foundations of inference
- foundations of probability in R
- dealing with missing data in R
- experimental design in R
- A/B testing in R
- fundamentals of Bayesian data analysis in R
- linear algebra for data science in R
- inference for categorical data in R
- Bayesian modeling with RJAGS

- analyzing survey data in R
- hierarchical and mixed effects models in R
- generalized linear models in R
- nonlinear modeling in R with GAMs
- factor analysis in R
- structural equation modeling with lavaan in R
- survey and measurement development in R
- anomaly detection in R
- analyzing US census data in R
- data privacy and anonymization in R

- introduction to text analysis in R
- string manipulation with stringr in R
- text mining with bag-of-words in R
- sentiment analysis in R
- Certificate

- introduction to the Tidyverse
- working with data in the Tidyverse
- project: Dr. Semmelweis and the discovery of handwashing
- modeling with data in the tidyverse
- communicating with data in the Tidyverse
- categorical data in the Tidyverse
- Certificate

- manipulating time series data with xts and zoo in R
- time series analysis in R
- ARIMA Models in R
- forecasting in R
- visualizing time series data in R
- case studies - manipulating time series data in R

- Correlation and regression fundamentals with tidy data principles
- K-means clustering with tidy data principles
- Bootstrap resampling and tidy regression models
- Hypothesis testing using resampling and tidy data
- Statistical analysis of contingency tables

- Regression models two ways
- Classification models using a neural network
- Subsampling for class imbalances
- Modeling time series with tidy resampling
- Multivariate analysis using partial least squares

- Model tuning via grid search
- Nested resampling
- Iterative Bayesian optimization of a classification model
- Tuning text models

- Create your own recipe step function
- How to build a parsnip model
- Custom performance metrics
- How to create a tuning parameter function
- Create your own broom tidier methods

- All Tidymodels Files