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Introductory Lessons:\n     * How to use jupyter notebooks\n     * Introduction to Pandas\n 2. Applied lessons:\n     * Input and Output - Questions\n     * Manipulation of Data - Questions\n     * Graphs - Questions\n     * Descriptive Statistics - Questions\n     * Linear Regression and Correlation - Questions\n\nEach lesson has a set of 5 questions which should be answered and self-marked. \n\n### Running the Textbook\n\nTo run the textbook simply click the links in the sections above. This opens a Google Collab of each lesson and question set.\n\nAlternatively, install the [Anaconda distribution](https://www.anaconda.com/) and open the `.ipynb` files with Jupyter Notebooks. \n\n### Funding\nThe 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. \n\nI worked at University of Bedfordshire as a research consultant to develop these materials under the guidance of Prof. Yanqing Duan.\n\n### Licence\n\nFeel free to use and edit this textbook under the guidance of the GNU General Public License v3.0.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fthomasjewson%2Fcci-data-science-textbook","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fthomasjewson%2Fcci-data-science-textbook","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fthomasjewson%2Fcci-data-science-textbook/lists"}