Importing data in R, data types and data wrangling
Visualization, grammar of graphics, ggplot2
PCA
Regression
Testing (ANOVA, t-test)
Clustering
Tidy data
R-Python interoperability
Basic python toolkit: pandas, numpy, matplotlib, seaborn
Data manipulation and preprocessing (Dealing with outliers, encoding features, scaling data)
Linear and non-linear models, Regression and classification
Metrics
Advanced ML and DNN (keras, torch, tf, building NN)
TBA, see the faculty expertise areas