If you have little to no experience as a data scientist, then you have to find a way to demonstrate that you have the skills to do the job. You can achieve this with a portfolio and this is arguably the most important part of your application. However, working on projects and putting together a […]
Probably the most valuable resource to me during my Masters research project was my notebook. I recorded everything about my project (meeting notes, analyses, ideas, theories, rough drafts) and even summaries of research papers that were interesting or relevant to my research. Since starting some data science projects outside of research and academia, I have […]
It’s easy to run headfirst into writing code and analysing data and forget about project layout, so make it part of your routine to get started with a simple structure that you either maintain throughout the project or evolve as you go. Future you (and others) will thank you for creating a well-structured, organised project. […]
Starting a new data science project (especially for the first time) can feel like a monumental task. You’ve probably read a bunch of data science articles or gone through an online course and you’re keen to apply your new-found knowledge to some actual data (that does not involve petal width). But where do you start? […]
If you’re starting your first (or next) data science project then chances are you’ll need to find one or more interesting datasets to analyse in your project. Well, look no further because I have a list of the best 5 places to look for great datasets to use in your project. The truth is you […]
Have you ever been really motivated to get stuck into analysing some data so you go ahead and download a really interesting dataset and (after a bit of googling) you import the data and go to town on it – you create summary tables, visualisations, fit a model, then go back to visualisations, then back […]