Python is very popular now, with simple syntax and powerful functions. Many students want to learn Python! Recently, many friends have asked me one after another, what should I do to learn Python, and what kind of position should I be in. The following are the worries of some students in our work circle:
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Change careers as early as possible (at the end of the article, there is a full set of python materials for free)
There are still many similar questions in the above group. I invited some guests from different positions to share their experience with you. Let me talk about my insights below:
1). Changing careers is like climbing a tree
You really have to change careers as early as possible. When you are young, the price of trial and error is very small. Even if you go the wrong way, you can switch back! After all, one doesn't climb a tree for too long, and it doesn't hurt to fall off. If you are old and you have climbed a tree for too long, you dare not come down! Afraid of falling, because it is too high and left the ground for too long, the courage to start again is not enough.
2). Scolding the post-80s generation
There is a joke on the Internet, saying that the boss can scold the post-80s employees desperately, but he dare not scold the post-90s employees. , the burden is heavy, and there is still a mortgage, so I dare not change jobs easily, so it doesn't matter if you scold me! But the post-90s can't do it, if you say you don't do it, you don't do it! The authenticity of this joke is not studied in detail, but it tells the crisis of many middle-aged programmers.
3).It's good to be young, but you must have a direction
The saying that youth is capital is true, especially in the Internet industry. When you are young, you have no family, you have more time, and you have plenty of physical strength and energy.
But most of them don't know what they like when they are young, and they don't know which path they should take. If you are lucky, you will enter a good unit or a good industry in your first job. It took 3 years to realize that I had taken a detour!
If you know that you have taken a detour, you are afraid that it will be 6-7 years before you find out that you have taken a detour and that the ship you are staying in is about to sink. What should you do? . .
4). Graduation for 3 years is critical
The gap between people is the 3-5 years after graduation. Especially in the industry of programmers, some people say that they are young people. I don’t agree very much, but I don’t deny it either! After the age of 35, programmers must not still be playing low-level code farmers, or at least not repeat work, they can try architecture, management, and operation! But you just can’t repeat coding year after year, day after day, without improvement or breakthrough, you just have 10 years of experience instead of 10 years of work experience!
The distribution of the number of recruits for Python positions
If you really want to enter the Python field, let's look at it from the perspective of data. After all, choosing which direction will have a better chance of winning. After all, you are most afraid of detours when changing careers. I simply analyze it from the number of jobs, the city and the highest annual salary (mean value).
1. The demand for Python positions
- The back-end development position is a large one, which is nearly half of the current demand for all Python positions, and the demand is 10 times that of crawler engineers.
- Followed by data analysis positions, second only to Python back-end development
- Data mining and machine learning are very similar, and they can be combined together, with a share of about 17%, but it is only half of the data analysis positions. It seems that AI positions are far from saturated!
- There are very few reptile jobs, and the demand for reptile jobs has gradually dropped, so if you want to switch to crawler, you need to think about it
2. Cities with the hottest Python recruitment needs
Basic Python positions are located in Beijing, Shanghai, Guangzhou, Shenzhen, and Hangzhou, where the demand in Hangzhou is significantly greater than that in Guangzhou.
3. The annual salary of Python positions
Here is a preliminary analysis of the sample data of more than 5,000 positions. I took the maximum annual salary and then took the average for statistics. It is found that the salary of AI positions is still far ahead. It is very common for a machine learning position to have an annual salary of more than 300,000 yuan. The better ones are 500,000 yuan, which is nearly 50% higher than the salary of data analysis positions and reptile positions. The salary of artificial intelligence is really fat!
The specific details of the three positions are as follows
1). Reptile posts
2). Data analysis positions
3).Machine learning and data mining
4). Back-end development
To sum up, the highest salary in the Python industry is the road of machine learning data mining. If the recruitment is relatively wide and the Python back-end development is used, the job will be easier to find because of the large amount of data! It’s fine if you just want to be a crawler if you want to change careers, because there are fewer and fewer positions for pure crawlers. Perhaps combining the two skills of crawlers and data analysis will have a greater chance of winning.
0 experience 0 foundation, how to learn technology to make money?
It is good to learn Python whether it is employment or sideline business to make money, but to learn Python, you still need a study plan.
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1. Learning routes in all directions of Python
The technical points in all directions of Python are sorted out to form a summary of knowledge points in various fields. Its usefulness lies in that you can find corresponding learning resources according to the above knowledge points to ensure that you can learn more comprehensively.
2. Essential development tools for Python
3. Python video collection
Watching zero-based learning videos is the quickest and most effective way to learn. Following the teacher's ideas in the video, it is easy to get started from the basics to the in-depth.
4. Practical cases
Optical theory is useless, you have to learn to follow along, and you have to do it yourself, so that you can apply what you have learned to practice. At this time, you can learn from some actual combat cases.
5. Python exercises
Check the learning results.
Finally, don't let go of the enthusiasm you started at that time, and become stronger and better together.