Administrative Information
| Title | Platforms |
| Duration | 2 x 45 mins |
| 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
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 |
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.