But this doesn't mean that we can't make the learning process efficient and interesting in some interesting ways.

The purpose of this paper is to provide an efficient learning path for all students who are studying data analysis, even those who have not yet started, so that more people can become professional data analysts smoothly and efficiently.

Before learning a technology, you should know what you want to achieve, that is, what problems you want to solve through this technology.

With this goal, you can know what its knowledge system is like before you can achieve this goal.

Hangzhou computer training/thinks that only by making clear the goal orientation and learning the most useful part of knowledge can we avoid invalid information and reduce learning efficiency.

If you want to be a data analyst, you can go to the recruitment website to see what the requirements of the corresponding position are. Generally speaking, you will have a preliminary understanding of the knowledge system.

The enterprise's demand for skills can be summarized as follows: basic operation of SQL database, basic data management, extraction, analysis and presentation of basic data with Excel/SQL, data analysis with scripting language, ability to obtain external data with PythonorR, such as crawler or familiar with basic data visualization skills in public data sets, ability to write data reports, and familiarity with commonly used data mining algorithms: regression analysis, decision tree, classification and clustering methods, followed by the process of data analysis. Generally, a data analysis project can be implemented according to the steps of "data collection-data storage and extraction-data preprocessing-data modeling and analysis-data visualization".

According to this process, the knowledge points that each part needs to master are as follows: What is an efficient learning path is the process of data analysis.

Step by step in this order, you will know what each part needs to complete, what knowledge you need to learn and what knowledge you don't need for the time being.

Every time you learn a part, you can have some practical results to output. With positive feedback, you are willing to spend more time in it.

With the goal of solving problems, the efficiency will naturally not be low.