Data Science I
This is a set of questions for a data scientist who pretends for the role of a junior specialist in a consulting or offshore development company. It is split into the 10 main parts:

- Logic: basic Boolean algebra and logical statements
- CS and Computing: Python fundamentals and O-notation
- Mathematics: basic calculus and algebra
- Probability Theory and Statistics: probabilistic events, the law of big numbers, etc
- Optimization: gradients and numerical methods essence
- General Predictive Modeling: foundations of statistical data modeling
- Machine Learning Algorithms: logistic regression vs SVM
- Neural Networks and Deep Learning: backpropagation, depth vs width
- Research and Frontiers: did you hear about arxiv?
- Communication and Presentation: basics of data visualization

Don't feel overwhelmed with the number of questions, most of them are easy and there is always a chance to guess :)
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