Insel-Login Aktuell gibt es Probleme beim Login mit Insel-Accounts via SWITCHaai (betrifft u.a. ILIAS, KSL). Die entsprechenden Stellen wurden informiert. Dozierende der Humanmedizin wenden sich bitte zwecks Folien-Upload an: studium.meddek@unibe.ch
Symbol Kurs

2022-08-30 - 2022-09-02 CAS ADS M2 Statistical Inference for Data Science (4 Days)

CAS Applied Data Science Module 2

Reiter

CAS Applied Data Science Module 2
 
See study plan on cas-applied-datascience.unibe.ch. 

Target group
  • Graduates and professionals enrolled for the CAS Applied Data Science 
Prerequisites 
  • University or University of Applied Sciences level degree (bachelor, master, phd) 
Methods
  • Lectures, tutorials, discussions, project work with poster presentation
Time : 2022-08-30 - 09-02 09:00 - 12:30 (afternoons for self studies) 
Onsite Location : University of Bern, Main Building, room 106. 
Online: Link

Presentation days: 2022-10-xx  (each participant only needs 0.5 day atttendance).

Language: English
Participants : Max 24
Registration : Mandatory (via Ilias)
Lecturer: Dr. Anja Mühlemann
Responsible : PD Dr. Sigve Haug
Module 2 Statistical Inference for Data Science
 
Tuesday 
09:00 - 10:30 Notebook 1 on descriptive statistics
10:30 - 11:00 Coffee Break
11:00 - 12:30 Introduction and discussions
12:30 - 13:30 Lunch
13:30 - 17:00 Notebook 2 on probability density functions ... (self study)
 
Wednesday 
09:00 - 10:30 Discussion session
10:30 - 11:00 Coffee Break
11:00 - 12:30 Parameter estimation, work on Notebook 3
12:30 - 13:30 Lunch
13:30 - 17:00 Self study

Thursday
09:00 - 10:30 Discussion session
10:30 - 11:00 Coffee Break
11:00 - 12:30 Hypothesis testing, work on Notebook 4
12:30 - 13:30 Lunch
13:30 - 17:00 Self study

Friday
09:00 - 10:30 Discussion session
10:30 - 11:00 Coffee Break
11:00 - 12:30 work on Notebook 5
12:30 - 13:30 Lunch
13:30 - 16:00 Self study
17:00 - 18:30 Apero       

2022-10-xx Presentation day
 
09:00 - 12:30 Presentations


During the CAS you ideally work on one or two datasets during all module works. You can

- bring your own dataset from research or work or private project
- or choose one from here : https://archive.ics.uci.edu/ml/index.php
- or choose one from here : https://www.kaggle.com/datasets

Not all datasets are equally well suited for all things to learn and practise in the CAS.
You are not supposed to read many books during this CAS, but of course you can. What you need to consult all the time is online documentation on all topics, google brings you there - and wikipedia of course.

This online book covers most of and more than Module 2. 

http://greenteapress.com/wp/think-stats-2e/
Dr. Anja Mühlmann

Anja holds a phd in statistics from the University of Bern, loves data science and coaching.

PD Dr. Sigve Haug

Sigve studied physics in Germany, Spain and Norway. He has been involved in neutrino physics experiments and high energy frontier experiments, often with main focus on the computing challenges related to the large and distributed data from these experiments. Today he is working for the Albert Einstein Center for fundamental Physics and the Mathematical Institute of the University of Bern where is leading the Science IT Support unit.