I saw a joke before:
In the past, when you went to interviews, HR would ask you " Are you proficient in office? "
Now when you go for an interview, HR will ask you " Can you do data analysis in Python? "
In the era of big data, whether it is data analysts, R&D, operations, marketing, or product managers, the ability to “ data analysis + data visualization ” is a basic requirement. The position of data mining engineer emerged as the times require and has become a scarce talent that the market is competing for!
Browsing the recruitment website, nearly 50% of the positions require " data analysis " capabilities. Python data analysis is widely used in manufacturing, finance, FMCG, e-commerce, medical and other industries, and is almost a must-have skill in the workplace. According to the information on the recruitment website, the salary of data analysts with about 1 year of experience is between 15-20k , and the salary of those with more than 1 year of experience is higher .
"Data analysis" and "data visualization" have become basic workplace skills for young people!
Machine learning and artificial intelligence may be the hottest topics in recent years, but in fact, whether it is artificial intelligence or machine learning, whether it is Alpha Dog that defeated Lee Sedol or various deep learning model algorithms, they are all a branch of data mining. Data mining is a method of implicitly extracting previously unknown and potentially useful data information. It is widely used and is the technical basis for numerous applications.
There are many methods of data mining . In addition to deep learning and various algorithm models, anything that can mine data and summarize useful results is called data mining. So, visualization, data analysis, looking at distribution, even just one shot Any rule base determined by your ass can be counted. Tools used for mining include Excel, seaborn, Tableau, SPSS, Numpy, Matplotlib , etc.
The combination of " mathematics + programming + business skills " is getting closer and closer, and enterprises have higher and higher requirements for compound application talents. People who understand data analysis can play a general role in the enterprise. They need to understand the essence through data and use data to guide the direction of the business.
Since data analysis is so important, how can we learn from it?
About Python technical reserves
Learning Python well is good whether you are getting a job or doing a side job to make money, but you still need to have a learning plan to learn Python. Finally, we share a complete set of Python learning materials to give some help to those who want to learn Python!
1. Python learning outline
The technical points in all directions of Python are organized to form a summary of knowledge points in various fields. Its usefulness is that you can find corresponding learning resources according to the above knowledge points to ensure that you learn more comprehensively.
2. Essential development tools for Python
3. Introductory learning video
4. Practical cases
Title 5: Python side job part-time and full-time routes
6. Internet company interview questions
This complete version of Python learning materials has been uploaded to CSDN. If you need it, you can scan the official QR code of csdn below or click on the WeChat card at the bottom of the homepage and article to get the method. [Guaranteed 100% free]
