Data science from scratch PDF

What is needed to start a career in Data Science

Knowledge of mathematical statistics, basic programming and data analysis skills are needed to enter any field in which a data scientist might be employed. The next steps will require more in-depth knowledge. The set of necessary skills and tools will largely depend on the tasks of a particular company. It is strongly recommended to start from a book like Data science from scratch by Joel Grus.

"Basic knowledge of machine learning, mathematical apparatus and programming is enough to solve simple tasks and get to the junior level. A middling and senor level specialist is already required to be able to fine-tune the parameters that affect the overall quality of the result. The list of sections from higher mathematics and understanding of the mathematical formulation of each model at this level is an order of magnitude higher than for a junior."

As a rule, Data Science uses SQL, Python, for complex calculations - C/C++. A good level of English will help you grow faster by reading professional literature and communicating with other industry professionals.

A developer's background is good for retraining as a datascientist. Developers know programming languages, understand algorithms, and have an understanding of the principles of tools in IT. In this case, the transition to a new specialty will take a few months. Important competitive advantages available to professionals from other fields: a better understanding of the subject area, strong communication skills.

The employer expects from an aspiring Data Science specialist:

• Basic knowledge of mathematical statistics, machine learning algorithms;
• skills in preparing data for analysis using libraries;
• Ability to choose the appropriate algorithm for the task and create a model based on it;
• ability to defend the effectiveness of the model;
• ability to successfully implement it in a process or product.

Let's get to the bottom of what Data Science is and how to build a career in data science.

Who can work in analytical projects

Back in 2012, analysts at McKinsey predicted a shortage of data scientists. In the U.S. alone, the shortage in 2018 was 140-190 thousand people. The shortage of managers who can ask analysts the right questions is even greater - 1.5 million people. The predictions were confirmed: there really is a shortage of specialists.