The editor feels that the most important point is that we must understand what basic skills the company needs for data analysts.

Only in this way can we be targeted.

I can roughly summarize it as follows: (1) Basic operations of SQL database, basic data management (2) Basic data analysis and display using Excel/SQL (3) Data analysis using scripting language, Python or R (4

) Have the ability to obtain external data, such as crawlers (5) Have basic data visualization skills and be able to write data reports (6) After being familiar with commonly used data mining algorithms: regression analysis, decision trees, random forests, support vector machines, etc., how can

It's up to the individual to arrange their spare time.

Generally speaking, learn the basics first, then the theory, and finally the tools.

Basically, every language must be learned in this order.

1. Learn basic knowledge of data analysis, including probability theory and mathematical statistics.

You still need to master the basics. If the foundation is not solid, the building of knowledge will fall down very easily.

2. Relevant theoretical knowledge of your target industry.

For example, in finance, you need to learn various knowledge such as securities, banking, finance, etc. Otherwise, you will be confused when you arrive at the company.

3. Learn data analysis tools, and combine the software with practical applications of cases. The mainstream software for data analysis includes (from easy to difficult): Excel, SPSS, stata, R, Python, SAS, etc.

4. Learn how to operate these software, and then use the software to process and analyze the data step by step, starting from data cleaning, and finally output the results, check and interpret the data.

If you really don’t understand, you can also find some video courses online.

Remember, the first step is essential and is the basis of data analysis.