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Welcome to Python for Data Science

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Getting Started

About the Course

WDSS’s Python for Data Science is the continuation of our Beginner’s Python course, taking a deeper dive into the use of Python for practical, data-centric work. The course focuses on the SciPy stack, a collection of Python packages used for data science, covering a wide range of applications from data visualisation to machine learning over. The course is composed of alternating rapid-fire teaching sessions, introducing new techniques and concepts, and slower-paced project sessions, in which participants can apply their newfound skills to practical, interdisiplary problems. In all, there are five teaching and project sessions, and two bonus sessions, giving you plenty of material to seek your teeth into.

Setup Guide

Now that we’re moving beyond a beginner’s level of Python, it’s time to leave Google Colab behind us and move on to using Python on our local machine. You can find a setup guide in the first bonus video from the session listing, walking through how to use Git, Conda, and Jupyter to complete the teaching notebooks and project work. Python can be notoriously difficult to setup, but once it’s done it’s done, so stick with it and ask for help if needed. By running code on our local machine and using Git (explained in the video), you will be able to save your work on GitHub, a good first step in building a portfolio to show to employers.

Issue Reporting

The WDSS team have put their heart and soul (and some hundreds of hours) into producing the material in this course. After devoting that much energy, we want the resources to as perfect as possible. For that reason, if you come across any issue (spelling/grammar mistake, incorrect code, confusing points), no matter how small, please report it here. It only takes a few moments and we’ll massively appreciate it!

Accessing Resources

Resource List

This course is jam-packed with content, which may make it seem a little daunghting at first but don’t worry. The teaching is designed in such a way that you can pick the content that is most relevant to you to tailor your learning experience. Here are the different types of resources avaiable and why you may or may not want to use them.

Teaching Notebooks

For the first iteration of the course, content will be taught live on Teams. This means that you need to attend these sessions every two weeks. In the session, the teacher will run through a teaching notebook, explaining new content and filling in blank code cells to provide examples. You are welcome to follow along with filling out the notebook during the session, or you can fill it out after. It is, however, advised that you fill it out at some point, as this is a critical step in commiting the new techniques to memory.

Project Notebooks

Following each teaching session, on alternating weeks, one of our subject ambassadors will run a project session. This is a chance to apply the teachings learnt in the previous session to real-world, interdisplinary problems. The class will be free-form, offering you the chance to work on the project independently and ask any questions where needed. A completed version of the project notebook will be released a day before the next teaching session.

Here you can find the resources for each session. Sessions will be added as the course progresses.

Further Reading

On top of any support the WDSS can offer, there are many open-source resources for learning Python. Here are some of our favourites:

Getting Help

FAQs

You can find a list of answered FAQs here.

Support Channels

Unlike our beginners’ courses, we do not currently have a mentoring scheme for this course. Instead, the course leader will arrange office hours for you to drop into and ask questions.

If you are self-teaching, feel free to reach out to Tim Hargreaves (the content author) on LinkedIn or Kasia Kobalczyk (the course coordinator) on LinkedIn

Contact

This course was written and initially taught by Tim Hargreaves.

Project sessions were developed by:

The current course coordinator is Kasia Kobalczyk.

For general enquires, reach out to education@wdss.io.

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