Demand for data scientists is ever increasing as industries are becoming increasingly data driven. Here are 5 practical tips anyone just getting started with data science will find useful.
Learn the prerequisites before jumping to machine learning and predictive modeling
Don't just focus on the end result of amazing predictive models, rather take the time to learn all the prerequisites so you can master the techniques behind them. This includes mathematics and statistics as well as any of the foundational steps other your algorithm.
Practice making simplified models that can be explained to less technical people
Having a good model is useless if you cannot explain to your client what any of it means. Your clients do not want to know about neural networks and hidden layers, all they care about is what the model can practically tell them.
Focus on the business problem over model accuracy
Sure, having an accurate model is great, but you also need to make sure you are looking at the correct and relevant variables. It is important to have a solid knowledge of tools and libraries, but being able to think in terms of the problem a business is trying to solve is where the magic happens.
Don't skim over data visualization and exploratory analysis
For this tip, the key is to practice as much as possible. It may be tempting to skip this step and just straight to model building, however that is a huge mistake. The more time spent getting to know the ins and outs of your datasets you will gain a much better understanding of the problems you are trying to solve.
Communication skills are key
The first thing that comes to mind when talking about data science is usually computer science and math related, however combining this with communication skills is what will really make you shine as an aspiring data scientist!