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VU Business Intelligence I (052411)

 
Tutor:  
 
First lecture: 04.03.2020 (attendance mandatory), 9:45, Last lecture: 24.06.2020. 
Wed. wkly. from 09:45 - 12:45  
Place: PC2, Währinger Straße 29 1.OG 

Contents

The course is structured into five sections: 
 

Dates

04.03.
Preliminaries
11.03.
Introduction and Modeling
18.03.
Data Provisioning, Exercise 1, on 9:45 join the live stream on discord
25.03.
Data Description and Visualization
01.04.
Discussion Exercise 1, Process Mining 1, Exercise 2
08.04.
Easter break
15.04.
Easter break
22.04.
Discussion Exercise 2, Social Network Mining, Exercise 3
29.04.
Discussion Exercise 3, Text Mining
06.05.
Probability distributions, sample statistics, law of large numbers, central limit theorem
13.05.
Quantiles, confidence intervals, fitting probability distributions
20.05.
Conditional probability, hypothesis (A/B) testing, conditional probability distribution, prediction task
27.05.
Regression and classification task, cost functions, linear methods, Bayesian linear methods, Naive Bayes. Deadline Exercise 4
03.06.
Tree-based methods, ensemble methods, support vector machines
10.06.
Neural networks and deep learning. Deadline Exercise 5
17.06.
Discussion Exercises 4 and 5, backup
24.06.
Final exam: Online interview

Live Stream

 

Deadlines:

 
 

Handouts

 

Exercises

Old Exams

Questions exam: statistics and machine learning part

 

Grading

Course is passed if >=50% of overall points 

Literature

Book Cover
Abbildung 1: Book Cover
Letzte Änderung: 18.06.2020, 08:35 | 627 Worte