Tilburg University (UVT) • Data Science: Business & Governance

As per request; a full cheatsheet with a single page of code and a page with notes. As the theoretical questions stayed relatively general, this should suffice. Practice the coding, understand what Gregorz asks you to do and ace the exam! Also, don't forget to bring your glasses. For me, it was perfectly readable, but I reckon for those with glasses, it might be slighly harder. I apologize. There is some minimal room left on the second page to write. I aso included some details from another mac...

Includes all lectures and summaries of articles for the Health Analytics course

Cheatsheet for Data Mining exam. (You can use 1 double sided A4)

CONTENT VERY SIMILAR TO 2019/2020 EXAM. Heard from many students that they passed the exam with the help from this document! Thanks for the feedback. Also have a look at my cheatsheet including code! A complete overview of all lectures, including slide snippets and additional notes for the course on Machine Learning by Dr. Gregorz. Hopefully, this should be enough to support you to understand the basics of Machine Learning as this document summarizes all lecture slides and everything he told....

MADE FOR THE 2018 EXAM, BUT BASED ON REVIEWS ALSO WORKED ON THE 2019 EXAM. CONTENT IS THE SAME (more or less, according to 2019/2020 students). Many have passed the exam with just this document. Best of luck studying! Original description: This document gives you a complete overview of this course. It includes textual information on the course, with the most important slides and diagrams included. Also, it contains several articles that weren't explained to my liking in the slides/lectures. ...

This summary is all you need to take with you to the open book exam. Every mandatory subject from the book 'Business Analytics' from James R. Evans plus extra information is in this summary. It tells you how to solve each question step-by-step, including the 'trick questions'. The lectures are known to be confusing and everything is simplified in this summary. Extremely helpful, especially when you have trouble understanding the subjects, or even math. All subjects: probabilities, distribution...

For the Machine Learning exam it is allowed to keep a cheat sheet of 1A4. This is specially made so that all subjects of this course are described in detail, such as Decision Trees, Perceptron, Gradient Descent, Feature Engineering, Logistic Regression and Neural Networks. You are allowed to bring cheat sheet (1A4) with you. On this cheat sheet, all the necessary information (and more) are available on just two sides of paper. The following subjects are included: Decision Trees, Perceptron, Grad...

Full summary including an introduction of Machine Learning and algorithms, such as Decision Tree, Perceptron, Gradient Descent, Logistic Regression (classifier) and Neural Networks. This summary also includes a section about Feature Engineering. Extra context and illustrations/graphs are also given, which makes this field of study a bit more understandable.

in the summary the differences between privacy and data protection are well explained. Furthermore, all lectures and articles that had to be read for lectures, including the 7 principles. Using this summary, I completed the course with an 8.5

Extensive and clear description for every topic of data processing. Explanation and screenshots of code. Handy for the exam. from 2016-2017.