I recall having a conversation with a colleague that went along the lines of, “How did anyone ever get anything done before Google?”. The truth is I doubt that I would be a data scientist if it wasn’t for Google’s magic hand. Whilst there’s not much more to say here besides, “Google it”, there are some tips and tricks that may be of use.
The first is, copy and paste the errors returned into Google. Remove the parts that are specific to your problem like ID’s or column names, but keep the rest. At the start of your career you’ll find no shortage of explanations and solutions.
Right click, then use “open in new tab” on the search results. Open 3-6 tabs, this will help you quickly cross reference answers without having to keep clicking back to the search results.
Close non-relevant unnecessary tabs before you make a search, these tabs just create more cognitive load that you don’t need. At the start I used to think that I’ll come back to this page so i’ll keep it open, 90% of the time I never did. If it’s a really important page then bookmark it. Worst case you can always pull up the page from your history.
Split screens work, always have an internet window accessible with Google opened to quickly search stuff whilst you’re working on a problem. If you don’t have multiple screens; most modern operating systems let you split your single screen.
Try not to overly rely on Google too much. If you find that you are constantly just copying and pasting code without understanding what’s going on then that’s a bad sign. Try and read multiple solutions, read information about the code as well as the code itself, once you are happy & have a rough idea of what’s going on – write your own code using the answers you found as an outline. You may think you are saving time by copying and pasting an answer from stackoverflow.com or Github, however you might be wasting time in the long run if you can’t come up with it yourself in the future.