Advanced AI in Businesses and Organizations

Advanced AI in Businesses and Organizations

Content

In this online course, students will implement an advanced machine learning project. The machine learning project should be of value to the decision-making in businesses, organizations, and society. This is an advanced course for specialization.

Students

• MMT
• MBR
• M.Sc.
  

Format

Online course via zoom

Dates

• Sat  13.11.2021  12:15-14:15  zoom  (introduction)
  
• Mon  07.03.2022  08:00-20:00  zoom
  
• Tue  08.03.2022  08:00-20:00  zoom
  
• Wed  09.03.2022  08:00-20:00  zoom
  
• Thu  10.03.2022  08:00-20:00  zoom
  

Seminar Paper

Deliverables will be a paper that involves actual machine learning results (with codes in the appendix). Students will need to advance their knowledge on their own with the provided materials.

Paper to be uploaded via moodle
Registration required: 13.12.2021 – 14.01.2022

Literature

• James, Witten, Hastie & Tibshirani (2013): An Introduction to Statistical Learning: With Applications in R. Springer. https://www.r-bloggers.com/in-depth-introduction-to-machine-learning-in-15-hours-of-expert-videos/
  
• Wickham: R for Data Science. O’Reilly. https://r4ds.had.co.nz/
• Kuhn & Johnson. Applied Predictive Modeling. Springer.
• Hastie, Tibshirani & Friedman. The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Springer.
• Goodfellow, Bengio, Courville (2016): Deep learning. MIT Press
• Blog: https://www.r-bloggers.com/ features regularly worked examples (with R)