Data Science in the Wild: Analysing Data with Python

31 Oct 2023, 12:00 – 14:00 17 Nov 2023, 12:00 – 14:00

Person sitting on rocks by water and writing in notebook

In Person

If you’ve ever tried to wrangle a dataset, you know that they can be wild. This two-class course is aimed at developing the skills to scope and implement preliminary data analysis at the early stages of a data science project. First, we will discuss the challenges around finding appropriate datasets and ensuring that they are used in an ethical manner. Then, we will go through some of the common challenges and pitfalls in data wrangling, while using Python libraries to demonstrate ways of overcoming these challenges. We will also discuss the use of data visualizations such as charts and tables for the purposes of better understanding your dataset. Finally, we will talk about data standardization, a useful step before running statistical or machine-learning models.

Some sample datasets will be provided, but since this course is entitled data science in the Wild, we encourage you to bring any tabular (structured) datasets that you are interested in understanding and using for your own projects.

At the end of this course, you’ll be ready to take on next semester’s more advanced machine learning courses. So get excited to wrangle your first challenge: the data beast!

This is a beginner-level course. No previous knowledge of the topic is required/expected and the trainer will cover the basics of each method.

After taking part in this event, you may decide that you need some further help in applying what you have learnt to your research. If so, you can book a Data Surgery meeting with one of our training fellows.

More details about Data Surgeries.

Those who have registered to take part will receive an email with full details on how to get ready for this workshop.

If you’re new to this training event format, or to CDCS training events in general, read more on what to expect from CDCS training. Here you will also find details of our cancellation and no-show policy, which applies to this event.

If you're interested in other training on data wrangling and data visualisation you can look at the following: