Administrative information

Title	Exploratory Data Analysis
Duration	60 min
Module	A
Lesson Type	Tutorial
Focus	Technical - Foundations of AI
Topic	Exploratory Data Analysis

Keywords

Data exploration,Python,Pandas,visualisations.,

Learning Goals

Learner can perform exploratory data analysis using Python.
Learner can use visualisations to investigate a variable's distribution using Python.
Learner can check for dependencies between variables by using visualisation in Python.

Expected Preparation

Learning Events to be Completed Before

Lecture: Exploratory Data Analysis

Obligatory for Students

Follow tutorial 1 to 5 of the notebook.
Read the following tutorials:
- Calculate statistics with Pandas
- Time series
- Text data
- Read chapter 3 and 4 of Python Data Science Handbook

Optional for Students

None.

References and background for students:

None.

Recommended for Teachers

Calculate statistics with Pandas
Time series
Text data
Chapter 3 and 4 of Python Data Science Handbook

Lesson Materials

The materials of this learning event are available under CC BY-NC-SA 4.0.

Instructions for Teachers

This is a hands-on session following the lecture Lecture: Exploratory Data Analysis. Students will work on a jupyter notebook. First they can work on pre-defined exercises and then they have to choose a dataset to explore on their own. You can also use choose to instruct the student to do the exercises before this session, so they can focus on the exploration of the dataset in this session.

More information

Click here for an overview of all lesson plans of the master human centred AI

Please visit the home page of the consortium HCAIM

Acknowledgements

The Human-Centered AI Masters programme was co-financed by the Connecting Europe Facility of the European Union Under Grant №CEF-TC-2020-1 Digital Skills 2020-EU-IA-0068.

The materials of this learning event are available under CC BY-NC-SA 4.0

The HCAIM consortium consists of three excellence centres, three SMEs and four Universities