At 28 years old, what has a temporary career change brought me?

I am 28 years old, graduated from an ordinary second-level university , male majoring in engineering, majoring in computer science and technology . I have been developing software applications for three years , and now I am doing Android development . I feel more and more out of my depth. Many technologies need to be learned from scratch. It is too stressful and I do not have much talent for learning.

I don’t feel very comfortable doing development, and I don’t have the ability to take a management position. I feel that as a programmer, I will change careers sooner or later. It’s better to change my career sooner rather than later. The time cost is not that big. I am currently considering changing careers, but I don’t know what I can do. (The story is relatively long, you should have a clear goal after reading it)
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The following careers come to mind right now:

  • Sales and business operations : I tend to have a neutral personality, I can’t drink at all, my communication skills are average, I don’t know if I’m suitable for this job
  • Software testing : I have never written test scripts or test cases. I only know about black box testing. I don’t know if anyone wants it. It seems that there is an age requirement for testing.
  • If you quit your job and open a cold drink shop or supermarket, or set up a street stall, or sell fruits, etc .: I don’t have enough funds, I don’t know how deep this industry is, and I don’t know if it can be done well.

I don’t know what kind of people outside companies usually recruit now. What occupations do people over 30 usually do when they go to work nowadays? The above is what I think of, I don’t know how people who have experienced it choose.
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Is it safe to learn Python by myself at the age of 28 and change careers?

It is difficult to change careers by self-learning Python with zero foundation, and it requires strong willpower. From a learning perspective, it is not too late to start learning Python programming at the age of 28, but from an employment perspective, it is relatively late to enter the industry.

Python language has been widely used in the current big data era . It is necessary for professionals to learn Python, especially for data-sensitive positions, such as statistical positions, market analysis positions, operations management positions, etc.

When you choose an industry, you often choose a life. The criteria for judging whether you like a job or not should be more diversified : salary, development, working style, interpersonal relationships, personal advantages, personality traits...all should be considered, the pros and cons should be weighed, and the lesser of the two evils should be considered.
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1. My classmates do projects and get money, but they also have to socialize every day and have the trouble of being exhausted at the construction site.

2. While the street civil servants are enjoying stability and fame and fortune, they are also burdened with trivial and unrealistic worries.

3. The big boss who sells fish always says that he regrets his life after making enough money. He only sells fish and lives in a dirty and messy environment for the rest of his life.

So there is no absolute good job , just see if it is suitable for you, experience more while you are still young, prepare for possible development, have a taste of impossible careers, and ask yourself more about what you want . Don't pay too much attention to the difficulty of changing careers and the time it takes. Once you find what you want, the most difficult step of changing careers has been overcome.
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For beginners, maintaining interest is the first priority in learning, and heavy tasks will kill interest; steps can be small, as long as you don't give up.

Switching to Python is the most successful thing in my life, and it is worth bragging about for the rest of my life.

Of course, if you want to switch to Python like me, then you must do what I say to avoid detours.

Learning Python is not difficult at all , because Java is much more difficult. I have told many people that the steps for learning Python are roughly as follows: Find a novice book that you think is suitable for you, because the books are all It’s hard to understand, but it’s okay if it suits you.

Find an experienced person to teach you. If you want to learn a programming language by yourself, the possibility is very small, and try not to do this kind of thing. If the probability is very small, try not to waste time.
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You must have a systematic study plan . This is very important. You must know what to study and what homework to do every day. Let me talk about it in detail:

1. Find a book that suits you. It should be a novice-level book . It shouldn’t be too difficult. Don’t learn too many things every day, which will disrupt your rhythm. You should learn Python step by step. Don’t be greedy for too much. If you learn it as soon as you get started, you will definitely have difficulty. , you will lose interest over time. For beginners, interest is very important, and it is important to have a book that suits you.
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2. There is a systematic learning course . It would be great if you have someone with very good Python skills around you. Many small problems can be solved. Because there are many detours that we don’t have to take. If others wake us up, it may take us half a day, but we don’t need to spend this time.
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3. Type code whenever you have time . Many people say this, but this is the truth about learning programming. Many people can read but not write. This is all from personal experience. There is no shortcut. Many people only want to read but rarely write. This is the same as not learning. Some have the perseverance to type through all the cases in the book. This is It's a stupid way to learn, but it's better than just reading and writing.

[I compiled a lot of Python learning materials when I taught myself Python before, but I can’t use them now. I uploaded them to the official CSDN. Friends in need can scan the QR code below to obtain them]

1. Study Outline

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2. Development tools

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3. Python basic materials

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4. Practical data

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Origin blog.csdn.net/Z987421/article/details/132776573