Modulbeschreibung

Applied AI

ECTS-Credits:
3
Lernziele:

The guiding idea is that AI is a powerful problem-solving tool and therefore every student needs to understand the fundamentals of AI to solve problems in their discipline. Hence, half of the module is used to teach the fundamentals of AI and the other half is used by the students to develop AI solutions to a problem from their discipline. The AI fundamentals are made understandable to students who neither have had higher mathematics, nor can program in a novel hands-on didactic approach. 

Kurse in diesem Modul

Applied AI:

Lernblock I

Introduction

  • What is AI & why is AI important?
  • Regression vs. Classification & Supervised vs. Unsupervised   

 

Lernblock II

Develop intuition

  • Probability is fundamendal
  • Develop intuition with tables
  • Find your own AI problem in your discipline with the help of the teaching staff 

 

Lernblock III

Unsupervised Learning

  • Clustering
  • Principal Component Analysis
  • Association Rules   

 

Lernblock IV

Supervised Learning

  • Linear Regression
  • k-Nearest Neigbors Classification 
  • Support Vector Machines
  • Decision Trees & Random Forests 
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Disclaimer

Diese Beschreibung ist rechtlich nicht verbindlich! Weitere Informationen finden Sie in der detaillierten Modulbeschreibung.