ashmathur91 / course-template

A template project for the Data Science courses.

Course name

Content

1. Description

2. Software

3. Bibliography

4. Description

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This repository is a template for the courses's repositories. Please, feel free to change whatever you think it could be better and notify it to the email list, mailto:[e-mail].

1.1. Repository structure

1.1.1. Lectures

Let's see first the structure of the repo. A regular course should have a folder for every lecture with the next construction:

Lecture #: A name

, and this is an example:

Lecture 1: A little example

If you can't find a name for the lecture, dont' worry. Just don't write it, and also don't use the colon ;)

Inside the lecture's folder of this repo you can find the template for the lectures.

1.1.2. Description of the course

The next thing is this file, the README.md file, which uses the Markdown syntax for being rendered. In GitHub, if a folder have a README.md file it will be rendered after the list of directories and files, regardless of the folder level.

This file should have four main parts:

• Course title and content.

• Description: A description of the course and how it will be studied.

• Other sections: This is the place for addiing other sections you could need that they aren't in this template.

• Software: A list with the software that will be used in the whole course. Please, write them as links and pin the version if is needed.

• Bibliography: Another list with any bibliography used in the course: books, papers, webs, etc. Please, use the MLA citation format. You can find this format for a lot publications in Google Scholar. Also, if only a few chapters of a book were used, mention them at the end of the cite.

You can find examples of the two last points in this very same file.

1.1.3. Whatever you need

If you need to add another files or folders that you think are relevant for communicate the content of the course, please add it. For example, if you want to show here the logo of the group, you can add an images foler to the root repo and set the image here:

1.2. Tutorials

Here is a list of some tutorials if you need to catch up with some of the technologies we will use for the courses's repositories:

• Git and GitHub: A 15 minutes interative tutorial by GitHub.

• Markdown: It's not a tutorial but a cheat sheet. In a 2 minutes quick reading you will dominate this useful syntax.

• Remark: The Wiki of this cool project for create slides only with Markdown.

2. Software

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• Python 2.7
• Pandas
• scikit-learn

3. Biblography

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• Stanton, Jeffrey M. "Introduction to data science." (2013).
• Zumel, Nina, and John Mount. "Practical data science with R." (2014). Ch 1 to 4.