Add web and slides form template generated version (#170)

* Add web and slides form template generated version

* Remove unused files

Author: stijnvanhoey

CONTRIBUTING.md

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 title: Data manipulation, analysis and visualisation in Python
-logo: 
+logo:
 description: Specialist course Doctoral schools of Ghent University
 show_downloads: true
-theme: jekyll-theme-minimal
+theme: jekyll-theme-minimal

_config.yml renamed to docs/_config.yml

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+---
+layout: default
+---
+
+# Contributing guide
+
+First of all, thanks for considering contributing to the course! 👍
+
+## How you can contribute
+
+There are several ways you can contribute to this course.
+
+### Share the love ❤️
+
+Think this course is useful? Let others discover it, by telling them in person, via Twitter or a blog post.
+
+### Ask a question ⁉️
+
+Trying out the material and got stuck? Post your question as an [issue on GitHub](https://github.com/jorisvandenbossche/course-python-data/issues). While we cannot offer user support, we'll try to do our best to address it, as questions often lead to the discovery of bugs.
+
+Want to ask a question in private? Contact the course maintainer by [email]([email protected]).
+
+### Propose an idea 💡
+
+Have an idea for to improve the course? Take a look at the [issue list](https://github.com/jorisvandenbossche/course-python-data/issues) to see if it isn't included or suggested yet. If not, suggest your idea as an [issue on GitHub](https://github.com/jorisvandenbossche/course-python-data/issues/new).
+
+### Report a bug 🐛
+
+Using the course and discovered a bug or a typo? That's annoying! Don't let others have the same experience and report it as an [issue on GitHub](https://github.com/jorisvandenbossche/Have an idea for to improve the course? Take a look at the [issue list](https://github.com/jorisvandenbossche/course-python-data/issues) to see if it isn't included or suggested yet. If not, suggest your idea as an [issue on GitHub](https://github.com/jorisvandenbossche/course-python-data/issues/new).
+/issues/new) so we can fix it. A good bug report makes it easier for us to do so, so please include:
+
+* Your operating system name and version (e.g. Mac OS 10.13.6).
+* Any details about your local setup that might be helpful in troubleshooting.
+* Detailed steps to reproduce the bug.
+
+### Contribute code 📝
+
+Care to fix issues or typo's? Awesome! 👏
+
+Some notes to take into account:
+
+- The course material is developed in the [course-python-data](https://github.com/jorisvandenbossche/course-python-data) repository. When updating course material, edit the notebooks in the [course-python-data](https://github.com/jorisvandenbossche/course-python-data) repository, the other ones (the ones used in the tutorial) are generated automatically.
+- the exercises are cleared using the `nbtutor` notebook extension: <https://github.com/jorisvandenbossche/nbtutor>
+
+
+

docs/contributing.md

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+# Data manipulation, analysis and visualisation in Python
+
+## Introduction
+
+The handling of data is a recurring task for data analysts. Reading in experimental data, checking its properties,
+and creating visualisations may become tedious tasks. Hence, increasing the efficiency in this process is beneficial for many professionals
+handling data. Spreadsheet-based software lacks the ability to properly support this process, due to the lack of automation and repeatability.
+The usage of a high-level scripting language such as Python is ideal for these tasks.
+
+This course trains participants to use Python effectively to do these tasks. The course focuses on data manipulation and cleaning of tabular data,
+explorative analysis and visualisation using important packages such as Pandas, Numpy, Matplotlib and Seaborn.
+
+The course does not cover statistics, data mining, machine learning, or predictive modelling. It aims to provide participants the means to effectively
+tackle commonly encountered data handling tasks in order to increase the overall efficiency. These skills are both useful for data cleaning as well as
+feature engineering.
+
+The course has been developed as a course for the Specialist course Doctoral schools of Ghent University, but can be taught to others upon request.
+
+## Course info
+
+### Aim & scope
+
+This course is intended for researchers that have at least basic programming skills. A basic (scientific) programming course that is part of
+the regular curriculum should suffice. For those who have experience in another programming language (e.g. Matlab, R, ...), following a Python
+tutorial prior to the course is advised.
+
+The course is intended for professionals who wish to enhance their general data manipulation and visualization skills in Python, with a specific
+focus on tabular data. The course is NOT intended to be a course on statistics or machine learning.
+
+### Program
+
+After setting up the programming environment with the required packages using the conda package manager and an introduction of the Jupyter
+notebook environment, the data analysis package Pandas and the plotting packages Matplotlib and Seaborn are introduced. Advanced usage of Pandas
+for different data cleaning and manipulation tasks is taught and the acquired skills will immediately be brought into practice to handle real-world
+data sets. Applications include time series handling, categorical data, merging data, tidy data,...
+
+The course closes with a discussion on the scientific Python ecosystem and the visualisation landscape learning
+participants to create interactive charts.
+
+## Getting started
+
+The course uses Python 3 and some data analysis packages such as Pandas, Seaborn, Numpy and Matplotlib. To install the required libraries,
+we recommend Anaconda or miniconda ([https://www.anaconda.com/download/](https://www.anaconda.com/download/)) or another Python distribution that
+includes the scientific libraries (this recommendation applies to all platforms, so for both Window, Linux and Mac).
+
+For detailed instructions to get started on your local machine, see the [setup instructions](./setup.html).
+
+In case you do not want to install everything and just want to try out the course material, use the environment setup by
+Binder [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/jorisvandenbossche/DS-python-data-analysis/HEAD) and open de notebooks
+rightaway (inside the `notebooks` directory).
+
+## Slides
+
+For the course slides, click [here](https://jorisvandenbossche.github.io/DS-python-data-analysis/slides.html).
+
+## Contributing
+
+Found any typo or have a suggestion, see [how to contribute](./contributing.html).
+
+## Meta
+Authors: Joris Van den Bossche, Stijn Van Hoey
+
+<img src="./static/img/logo_flanders+richtingmorgen.png" width="79%">
+<img src="./static/img/doctoralschoolsprofiel_hq_rgb_web.png" width="20%">
+