Administrative information

Title	Platforms
Duration	2 x 45
Module	A
Lesson Type	Practical
Focus	Practical - AI Modelling
Topic	Data analysis

Keywords

basic Python,basic Pandas,variables,lists,strings,tuple,data loading from csv,data lookup,

Learning Goals

To be able to use jupyter notebooks
To be able to use basics of Python (variables, lists, strings, tuple)
To be able to use basics of pandas (data loading from csv, data lookup)

Expected Preparation

Learning Events to be Completed Before

None.

Obligatory for Students

None.

Optional for Students

None.

References and background for students:

None.

Recommended for Teachers

None.

Lesson Materials

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

Instructions for Teachers

This learning event consist of laboratory tasks that shall be solved by the students with the help of the leading instructor.

You can base this class around the Notebooks.

Outline/time schedule


Duration (min)	Description	Concepts
45	Python	variables, lists, strings, tuple
5	pandas	data loading from table
10	pandas	data / table information: head, shape, info
5	pandas	df.loc
5	pandas	df.iloc
5	pandas	df.str.split
5	pandas	date conversion
10	pandas	groupby, sort

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