Machine Learning and Persuasive Systems design

Lecturer: 
Prof. Maurits Kaptein
Date: 
11.10.2021 09:30 to 12.10.2021 17:30
Place: 
Online

Registration

In weboodi:

https://weboodi.oulu.fi/ (course code 816616J)

Course synopsis

In this two day course we will examine various machine learning (and statistical learning) methods and their relationship to persuasive systems design. When designing personalized persuasive systems, often the personalization is based on user data, hence, a proper understanding of modern data science methods is key for successful personalized persuasive systems design. This course will cover supervised learning and reinforcement learning (multi-armed bandit problems), and it will explore recent approaches to causality. In each case the connection with persuasive systems design will be made. The course will combine theory with practice (you will use [R] for various machine learning methods).

Moodle space 

https://moodle.oulu.fi/course/view.php?id=10102

 

Course overview

This 2-day course will consist of several lectures and a number of hands-on exercises. The table below gives an overview of the activities and timeslots:

Time

Activity

Explanation

Monday, October 11

09.30-10.30

Lecture

An introduction to machine learning. This introduction lecture will introduce supervised learning, unsupervised learning, and reinforcement learning.

11.00-12.00

Lecture

Supervised learning. In this lecture we will dive into the details of supervised learning and its use for persuasive systems design.

13.00-14.00

Tutorial

Getting started with R. In this interactive session you will install the R software for data analysis and do your fist analysis project.

14.30-15.30

Lecture

Multi-armed bandits. In this lecture we will cover Mult-Armed Bandits and their use in the design of personalized persuasive systems.

15.30-16.00

Assignment

Introduction of assignment 1. (Supervised learning)

Tuesday, October 12

09.30-10.15

Feedback

Feedback / intermediate questions assignment 1

12.30-13:30

Discussion

Discussion assignment 1 + Introduction assignment 2

14:00-14:30

Feedback

Feedback / intermediate questions assignment 2 (Multi-armed bandits)

16:30-17:30

Discussion

Discussion assignment 2 + Closing

 

Please note that all the lectures take place online.

Software

For this course we will use the R software package for data analysis. To make sure you are prepared:

 

Questions / comments

Akon Ekpezu (Akon.Ekpezu@student.oulu.fi) and the lecturer (prof.dr. Maurits Kaptein) can be reached at m.c.kaptein@uvt.nl.

Last updated: 1.10.2021