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This is a repository for materials used for a module on quantitative research resources, taught at Glasgow International College at The University of Glasgow.

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CRASH COURSE PYTHON FOR DATA SCIENCE - ALL MATERIALS LIVE HERE!

This is a repository for materials used for a module on quantitative research resources, taught at Glasgow International College at The University of Glasgow.

WHAT IS PYTHON?

Python is a powerful programming language used for many different applications. A huge community around this open source language has created quite a few tools to efficiently work with Python for Data Science. Python is becoming the laguage of choice of anyone interested in analysing data.

PREPARATION BEFORE THE SEMINAR

To follow the Python tutorial during our seminar, you will need to have a few things installed.

The reason we do this before the seminar is because it takes time. And we only have two hours. So I would much rather we spend those hours actually learning Python and its application in Data Science instead of troubleshooting a Python installation gone wrong!

That's why I'm asking you to go through this initial steps before the seminar. So we can get started right away!

Python instalation and setup for Mac & Windows

To install and setup Python for Mac and Windows, follow the steps in this tutorial.

When you are finished, come back and continue with these instructions.

Visual Studio Code

To open the folder with the Workshop and exercise notebooks, you will need an IDE (Integrated Development Environment). There are many popular IDE environments for Python development. But I use Visual Studio Code.

Why VS Code?

  1. VSCode has support for most of the popular languages. 😍

  2. The community is huge and has plugins for every kind of language. 💖

  3. It has integrated terminal for faster development and takes less storage and has low memory footprint. 🙂

To install VS Code you will have take to follow some steps:

Once you have finished installing VS Code, you can continue with these instructions.

Download the materials into your local working environment (fancy way of saying your laptop!).

  1. Download this repository (https://github.com/gracecarrillo/Python_Crash_Course) as a zip file, save it in the folder you will be working on, and unzip it. If you're not sure how to do this, see this resource about how to unzip a file in a Mac, and this resource for Windows.

Make sure you save this folder in a location you will remember.

  1. You also need to install the Jupyter Extension to work with the notebooks that we will use during this workshop. These notebooks are called Jupyter notebooks, and they are useful to combine python code and text in the same file. You can learn more about Jupyter noteboooks by following this link..

To begin adding the Jupyter Extension to your VS Code IDE, follow this link.. You will see the following window:

Click Install. When a pop-up window asks you if you want to open Visual Studio Code, just click the button to open it. This will take you to your VS Code. You will see the following, except that for you, the button will say Install instead of Unistall, like it does for me.

Open the materials.

You should now be ready to get started! Verify this by navigating to the Python_Crash_Course folder you downloaded. Go to File -> Open Folder ...

Select the folder and click Open. You should now be able to see all the folders for this course.

Happy learning!

WHAT TO DO AFTER THE SEMINAR

  1. EVIDENCE FOR E-PORTFOLIO: Complete the Workshops and Exercises in order. Do as many as you can and take screenshots of your local setup with the exercises. You don't have to finish them all, just do as many as you can. You can reflect on your experience doing the exercises in your reflective log for the e-portfolio.



Course Instructor: Graciela Carrillo

Module Coordinator: Dr. Molly Huq



Other Resources

Python Beginner Tutorial. Full playlist: 26 videos

Learn Python - Full Course for Beginners

Intermediate Python.

Python Object Oriented Programming (OOP). Full playlist: 6 videos


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This is a repository for materials used for a module on quantitative research resources, taught at Glasgow International College at The University of Glasgow.

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