TL:DR - This is a short, interactive textbook aimed at introducing data science to non-IT university undergraduates.
The textbook has 7 lessons with the following structure:
- Introductory Lessons:
- How to use jupyter notebooks
- Introduction to Pandas
- Applied lessons:
- Input and Output - Questions
- Manipulation of Data - Questions
- Graphs - Questions
- Descriptive Statistics - Questions
- Linear Regression and Correlation - Questions
Each lesson has a set of 5 questions which should be answered and self-marked.
To run the textbook simply click the links in the sections above. This opens a Google Collab of each lesson and question set.
Alternatively, install the Anaconda distribution and open the .ipynb
files with Jupyter Notebooks.
The content for this textbook was funded by the European Commission’s Erasmus+ via a scheme called ‘Computing Competences – Innovative learning approach for non-IT students’ (CCI) – a project which University of Bedfordshire collaborated on.
I worked at University of Bedfordshire as a research consultant to develop these materials under the guidance of Prof. Yanqing Duan.
Feel free to use and edit this textbook under the guidance of the GNU General Public License v3.0.