Predicitve Analytics with R
In this course, you will learn how to import, clean, manipulate, aggregate, and visualize data, as well as build predictive analysis models. As part of this, interactive, practical learning sessions are designed to give you in-depth hands-on experience with various R packages, including ggplot2, dplyr, readr, tidyr, dials, yardstick, and tidymodels. Having mastered relevant data preprocessing skills, you will also learn to build machine learning models to solve various classification, regression, and clustering problems on real-world datasets.
- Foundations of R for Data Science
- Data Wrangling with dplyr package
- Data Cleaning with tidyr package
- Data Visualiziation with ggplot2 package
- Explorative Data Analysis with ggplot2 package
- Feature Engineering with recipes package
- Cluster Analysis with different packages
- Regression with tidymodels package
- Classification with tidymodels package
- Hyperparameter Optimization with dials package
- Performance Evaluation with yardstick package
Date and time
The class will begin on Friday, May 20, 2022 and run for five weeks on Fridays between 2:00 and 4:00 pm s.t.
Assignments, group project and presentation