
In this lecture, we're going to get your coding environment setup. We'll get a Jupyter Notebook up and running and take a very quick tour of one. If you already have a preferred development environment, by all means continue with that. This lecture is mainly to help people new to coding get setup.

We'll be using Python within the Jupyter notebook development environment in this course. Jupyter notebooks offer us a way to write executable Python code, typeset text (with Latex) and plot data visualisations, all in one file. This is a huge advantage over traditional development environments where we can typically only write code. Jupyter notebooks are a great way to write and document your code and are extremely popular within data science and engineering. Once you start using Jupyer notebooks for data analysis and modelling it's very hard to go back to only using a standard IDE or code editor.

Follow along with me in the video above to download Anaconda and get up and running. If you run into trouble, get in touch by following the link to the lecture comments. You can find the link in the resource panel at the top of the lecture (under the video).


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