University College Ghent
Geraard de Duivelstraat 5 - 9000 Ghent - Belgium
Phone: 09 243 33 33 - E-mail: info@hogent.be
Website: www.hogent.be
Data Science & AI37555/4707/2122/1/68
Study guide

Data Science & AI

37555/4707/2122/1/68
Academic year 2021-22
Is found in:
  • International Curriculum IT, programme stage 2
This is a single course unit.
Study load: 4 credits
Weight: 4,00
Total study time: 100,00 hours
It is not possible to enrol in this course unit under
  • exam contract (to obtain a credit).
  • exam contract (to obtain a degree).
Special admission is required to enrol in this course unit under credit contract.
Co-ordinator: Van Vreckem Bert
Other teaching staff: Lievens Stijn
Languages: English
Scheduled for: Semester 2

Final objectives

The student is able to reflect in a problem-solving way by capturing, analyzing, visualizing and interpreting data in order to arrive at insights and suitable models to support the policy of the organization

Objectives

Knows some descriptive measures for data.

Is able to calculate some descriptive measures for data using statistical software.

Knows different types of plots to represent data visually.

Is able to visualize data using the appropriate plots

Knows the basic rules regarding calculating with probabilities.

Knows the properties of some important probability distributions.

Is able to quantify and appropriately test the relationship between two variables.

Is able to create a simple linear model to show the relationship between two or more variables.

Is able to discuss some common models for predicting time series and / or detecting anomalies.

Is able to indicate the importance of testing the accuracy of a model in a methodologically correct way.

 

Contents

Basic rules of probability theory.

Tables, graphs, measures, indices, probabilities, probability variables, probability distributions, samples, statistical modeling, estimation, sample length and reliability of statements, hypothesis tests, time series (trends), regression, correlation

Perform statistical analysis using Python

 

Organisation of education

Contactonderwijs36,00 hours

Teaching methods

  • Learning dialogue
  • Practice session
    Additional information: supervised exercises

Study guidance

The students get the possibility to consult the teacher for a specific substantive problem (consultation)

Evaluation

Evaluation(s) for first exam chance
MomentForm%Remark
Inside Regular exam scheduleWritten examination100,00open book using a PC
Evaluation(s) for re-sit exam
MomentForm%Remark
Inside Regular exam scheduleWritten examination100,00open book using a PC
This course unit is marked out of 20 (rounded to an integer).
Re-sit exam: is possible.

Prerequisites

The student should be able to program in at least one programming language, preferably Python.
The student should have some basic mathematical knowledge so that simple mathematical formulas can be interpreted.
Possible deadlines for learning account: 15.03.2022 ()