Applied Machine Learning with R
Short Course

Machine learning is one of the most important and disruptive technologies today, in industries ranging from pharma, to insurance, to marketing. In this course, you will learn how to apply machine learning techniques to data using the R statistical language. You will learn the basics of the machine learning process, from acquiring and exploring data, to selecting and implementing machine learning models, to evaluating their performance. We will cover the most common machine learning problems (regression, classification, and clustering), and introduce you to popular algorithms for solving these problems such as regression, decision trees, and deep learning. We will cover applied examples such as medical diagnoses, hiring decisions, demand forecasting and marketing campaigns.

The course will take place from 9:00 to 18:00 on each course day. Each day will contain a series of short lectures and examples to introduce you to new topics. The bulk of each day will be dedicated to hands-on exercises to help you ‘learn by doing’. Dedicated time will be given for 1:1 feedback. All course materials, tutorials, examples, exercises, and solutions will be available online for you to view at any time during, and after the course.

Participants are requested to bring their own laptop with software installation rights. There are no strict knowledge prerequisites for this course. Prior experience with a programming language (e.g.; SAS, R, STATA), as well as an introductory course in statistics, is helpful but not necessary.

  • Nathaniel Phillips, PhD
  • Dirk Wulff, PhD

CHF 1,490

Course starts on:
Saturday, 19.01.2019
Course ends on:
Sunday, 20.01.2019

Department of Psychology, University of Basel

Fields marked with * are mandatory

Location

Advanced Studies Steinengraben 22, 4051 Basel

to top