What are good learning resources to help me prepare for test and interviews?
Good resources, among many others, are:
- John Hopkins University Data Science course at Coursera
- Microsoft Professional Degree in Data Science (currently Beta release)
- Startit.rs and DataScience.rs courses, such as Intro to R for Data Science
- Mathematical Statistics with Applications (for basics of statistics)
- An Introduction to Statistical Learning (for machine learning, though there are many other good books as well)
- Time Series Analysis (for introduction to time series analysis)
When it comes to programming/technical languages needed, there are many tools which would enable you to finish the test
successfully, Python, R, MATLAB, SQL, etc. There is an extraordinary amount of good literature and courses for each of
these, we wouldn’t favor any of them here.
Can you give me some advice on preparing myself for the test?
Be curious. Download datasets interesting to you (there are many good resources for these, e.g. kaggle.com), ask yourself
questions and try to draw some conclusions. Focus on answering the question you asked rather than doing some complex
analysis (if there is a trade-off between these). In order to do this, it is important to pick a question which generally
interests you – the problem is much harder if you’re not having fun in the process.
What are the areas we can expect at the test?
There are two parts of the test – eliminatory and exploratory. Exploratory part is completely up to you – you have the
freedom to implement any techniques you are comfortable with. For the eliminatory part, it consists of a set of specific
questions for which you need statistical skills in order to solve them.