AI for Managers
Content
Students
Format
Dates
- Fri 12.11.2021 08:00-20:00 zoom
- Sat 13.11.2021 08:00-20:00 zoom
- Fri 19.11.2021 08:00-20:00 zoom
- Fri 26.11.2021 08:00-20:00 zoom
Exam
Literature
- James, Witten, Hastie & Tibshirani (2013): An Introduction to Statistical Learning: With Applications in R. Springer
- Sharda, Delen & Turban (2014): Business Intelligence: A Managerial Perspective on Analytics. Pearson
Enrolment
Moodle self enrolment, enrolment key via LSF- Trainer/in: Stefan Feuerriegel
- Trainer/in: Dennis Frauen
- Trainer/in: Valentyn Melnychuk
- Trainer/in: Katharina Riepl
- Trainer/in: Simon Schallmoser
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)
Enrolment
Moodle self enrolment, enrolment key via LSF
- Trainer/in: Stefan Feuerriegel
- Trainer/in: Valentyn Melnychuk
- Trainer/in: Katharina Riepl
- Trainer/in: Simon Schallmoser
Research in AI and Management
Content
The online course aims to give an overview of current trends in AI research. The weekly sessions consist of 45-60 minutes of presentation (e.g. presentation of a "paper in progress") followed by an opendiscussion, feedback and QA.
Students
- MMT
- MBR
- M.Sc.
Format
Dates
Please find all dates, speakers, topics, etc. on our website.
28.10.2021 | 12:00-13:30 | Zoom |
---|---|---|
04.11.2021 | 12:00-13:30 | Zoom |
11.11.2021 | 15:00-16:30 | Zoom |
18.11.2021 | 12:00-13:30 | Zoom |
25.11.2021 | 12:00-13:30 | Zoom |
02.12.2021 | 12:00-13:30 | Zoom |
09.12.2021 | 12:00-13:30 | Zoom |
16.12.2021 | 12:00-13:30 | Zoom |
23.12.2021 | 12:00-13:30 | Zoom |
13.01.2022 | 12:00-13:30 | Zoom |
20.01.2022 | 12:00-13:30 | Zoom |
27.01.2022 | 16:00-17:30 | Zoom |
03.02.2022 | 12:00-13:30 | Zoom |
10.02.2022 | 12:00-13:30 | Zoom |
Exam
Enrolment
Moodle self enrolment, enrolment key via LSF- Trainer/in: Stefan Feuerriegel
- Trainer/in: Valentyn Melnychuk
- Trainer/in: Katharina Riepl
- Trainer/in: Simon Schallmoser
Introduction to AI
Content
Students
Format
Dates
- Fri 05.11.2021 08:00-20:00 zoom
- Sat 06.11.2021 08:00-20:00 zoom
- Fri 12.11.2021 08:00-20:00 zoom
- Fri 19.11.2021 08:00-20:00 zoom
Exam
Literature
- James, Witten, Hastie & Tibshirani (2013): An Introduction to Statistical Learning: With Applications in R. Springer
- Sharda, Delen & Turban (2014): Business Intelligence: A Managerial Perspective on Analytics. Pearson
Enrolment
Moodle self enrolment, enrolment key via LSF- Trainer/in: Stefan Feuerriegel
- Trainer/in: Dennis Frauen
- Trainer/in: Valentyn Melnychuk
- Trainer/in: Katharina Riepl
- Trainer/in: Simon Schallmoser