Can you learn data analysis from scratch?

Do you want to learn data analysis from scratch?

1. How long does it take to learn data analysis?

Everyone’s learning ability and foundation are different, so the learning cycle of data analysis is also different. Moreover, the content of study must be selected based on one's own development direction, so the study time will vary greatly. Generally speaking, it will take nearly three months at the fastest for learners with no basic knowledge to undergo systematic training. Here I would like to recommend the "Data Analysis Course that Everyone Can Learn" from Boxue Valley, which focuses on cultivating the data processing capabilities, data analysis capabilities and data mining capabilities of data analysts. The course content covers database management, statistical theory methods, data Analyze the application of mainstream software to data mining algorithms, etc., and systematically explain a set of data analysis process technologies. After completing the course, learners can directly reach the level of intermediate data analysts.

2. What should we learn about data analysis?

(1)Statistics

Statistics is the basis of data analysis and is an important content that beginners must master with zero foundation. Learning the most basic statistical knowledge can solve most of the daily analysis needs, so it is highly recommended for beginners to start with statistics. Statistics design probability, distribution, sampling, linear regression, time series, statistical inference, etc.

(2)SQL

SQL is one of the core contents of zero-based learning data analysis. When the data you want to analyze exceeds one million levels, you need a database to solve it, and obtaining data from the database relies on the SQL language. You can use MySQL as a learning object, briefly understand some basic database principles such as database paradigm design, and focus on learning the SQL language. You can install a MySQL database yourself for practical exercises.

(3)Excel

Speaking of Excel, some people may think it is very simple, but Excel is indeed a powerful tool. As a core tool for data analysts, the specific learning content includes Excel function skills (search functions, statistical functions, logical functions), Excel quick processing skills (format adjustment, search positioning, shortcut key skills, etc.) and Excel visualization skills (combination charts, Bar charts, data bubble maps).

(4)Data mining, machine learning

This part can be studied optionally. Because statistical analysis can basically solve 70%-80% of the needs of daily data analysis work, and data mining and machine learning are more difficult and the threshold is slightly higher. This part is mainly about understanding the basic concepts and theories of data mining and machine learning. For example: classification, clustering, regression, decision tree, Bayes theorem, etc.

(5)Python

Because Python has many third-party powerful libraries, Python is a powerful tool for data analysis and a must-learn programming language for data analysis. For example, Numpy, Pandas, Matplotlib and python plotting, Sklearn and machine learning basics, etc. Although Python is an important tool for data analysis, the degree of Python mastery varies according to different career development directions.

(6)Product operation knowledge

Some people may have heard of the position of product operation. For data analysts who want to develop into a management route, product operation is a must-learn knowledge. In fact, product operation knowledge is not complicated. It means breaking down the indicators to the smallest detail according to your own business needs, and then using two data analysis methods: year-on-year and month-on-month.

I am not a mathematics major or a statistics major. If I want to engage in data analysis, I can do it myself

OK. . . . But you really need to hold on

I was a psychology major at first, and later I learned it by myself because I used data analysis in a market research company,

I learned almost all of spss by myself, but at the beginning I was looking for textbooks and practicing at the same time. I found time to study every day during work hours, and I also studied almost after I got home from work. I basically had no spare time, and my spare time was mainly based on studying. , except on Sundays I will take a break and go shopping

Amos is the same. For SAS, I suggest you learn it without any foundation. It is still very difficult. Anyway, I have not learned SAS because the basic commonly used spss can solve it. I am also learning SQL by myself now because I am free from work recently and I go to work every day. I just read and practice. I still read and practice after get off work in the evening. I bought a book "SQL in a Simple Language". I have finished reading half of it now, and I have basically mastered the previous parts.

This is my experience. If you want to learn, you must persist and use all the time.

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