Predicitve Analytics with R

Introduction

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.

Lecturer

Dr. Nijat Mehdiyev
E-Mail: nijatsamiloglu.mehdiyev[at]uni-saarland.de or nijat.mehdiyev[at]dfki.de
The course is offered by the Institute for Information Systems (Iwi) at Saarland University.

Content

  1. Foundations of R for Data Science
     
  2. Data Wrangling with dplyr package
     
  3. Data Cleaning with tidyr package
     
  4. Data Visualiziation with ggplot2 package
     
  5. Explorative Data Analysis with ggplot2 package
     
  6. Feature Engineering with recipes package
     
  7. Cluster Analysis with different packages
     
  8. Regression with tidymodels package
     
  9. Classification with tidymodels package
     
  10. Hyperparameter Optimization with dials package
     
  11. 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.

Grading

Assignments, group project and presentation

Registration

If we have aroused your interest, please register by sending your contact information and a short message to nijat.mehdiyev(at)dfki.de or nijatsamiloglu.mehdiyev[at]uni-saarland.de