Research Information System
Description
The course aims to introduce students to the fundamental concepts and
practical applications of artificial intelligence (AI) and R programming in the
field of computational applied psychology. The course will cover various topics,
including the foundations of AI, supervised and unsupervised learning
techniques, natural language processing (NLP), and the use of R for data
analysis and visualization. Additionally, the course will explore case studies
and applications of AI in computational applied psychology, allowing students
to understand how these technologies are leveraged to address psychological
challenges and improve outcomes.
Objectives
Understanding the principles and applications of AI in computational applied
psychology, including the terminology and concepts.
Gaining proficiency in applying supervised and unsupervised learning
techniques using R, preprocessing data, training machine learning models, and
interpreting the results.
Utilizing natural language processing (NLP) for psychological text analysis,
performing tasks such as sentiment analysis and text classification.
Developing skills in effectively using R for data analysis and visualization,
employing tools like ggplot2 to create visual representations of psychological
data and communicate findings.
Learning outcomes:
By the end of the course, the student will be able to
LO1. Interpret the principles and applications of AI in computational applied
psychology.
LO2. Articulate supervised and unsupervised learning techniques using R.
LO3. Devise natural language processing (NLP) for psychological text analysis.
LO4. Programming R for data analysis and visualization.