Intro to the Course

About the Course

Machine Learning is a very hot topic for Economist and Business majors
Difficulty of the Course
- For the course:
  - Matrix Algebra is not required and will not be used
  - Calculus is not required and will not be used
  - Programming knowledge is not required. The basic R knowledge you need is introduced in class and in the book.
- Support
  - Everybody can get a good grade! Do the work and ask me for help if needed (I will spend all the time needed with you)
Materials
- The book is available for free online: https://econ.lange-analytics.com/aibook (user name: aibook, pw: I let you know in class). Shameless self promotion. You can buy the book from Francis & Taylor starting October 2023.
- Presentation slides are available online at https://aibookslides.netlivly.app

Before class (+/- 0:45h)
- read related chapter online before class (you can quickly read over the interactive sections)
- do not use a phone — tablet with decent size is OK
- if there is something you do not understand (possibly make a note) and keep on reading — no problem
Do not miss class sessions!
- in class I walk you through the topics step by step.
- you can ask questions about each topic you are interested in or you like to get more information.
- you will do exercises in class and I will help, if you get stuck.
After class (+/- 1.5h)
- read the book chapter again
- read it at a computer with R and RStudio installed
- follow the interactive exercises in RStudio
- write down questions you have and ask them next time in class

Good grade
You get an understanding of machine learning that enables you:
- to talk about machine learning algorithms during an interview
- to use machine learning on your Senior Project/Master Thesis
- to build on the knowledge from the course by reading more advanced articles and watching videos to become an expert.