It is easy for beginners to give up when they are not taught Python. First of all, I would like to summarize my Python learning and development experience in the last two years. I have encountered some problems, and you should first face these problems, because more than 90% of people will encounter these problems when they are learning Python.
Article reprinted: Le Byte
① There are many online materials for self-study, but the quality is uneven;
② The information is messy and not systematic, and the lack of enterprise-level project actual combat;
③ There are too many application directions, there is no comprehensive learning path do not know how to choose;
④ No one with problems, can only grope, and finally forced to give up;
These problems, by no means unique, I believe many people have encountered, even feel that they are not suitable for development.
You need an experienced Python engineer to give you advice rather than trying to figure it out. Learning encounter bottlenecks or don’t know how to begin to learn a small white, you can add some learning exchange group, great god will be glad to, also will not regularly to share public live class, a lot of problems can solve online, group also has a necessary learning based video data and the latest books, don’t need to go online to find, have been packed, Meng New can find group administrator to get ↓↓↓
Latest Book + Video
After understanding the basic knowledge, it is to follow the learning path established in the second step, upgrade all the way to beat strange, learning mind map can be asked for free from the instructor teacher.
Python Mind Map
There are three things you need to think about when learning Python: I’ll show you how to solve these problems efficiently
1. What problems should I solve when learning Python?
2. What do you want to do after learning Python? How to plan your learning path
3. What do you want to learn?
Python is just a programming language, and it’s far too broad to figure out how to use it to solve problems. After you have learned the basics of Python, you must know where you want to go, and the path will vary depending on which direction you want to go.
I’m going to learn how to do data analysis in Python. I’m going to learn how to do data analysis in Python. I’m going to learn how to do data analysis in Django, the Flask framework.
This truth, like we want to travel to Thailand, certainly will not buy the ticket to Japan, very simple, but we have to admit that there will still be some people confused, come up on the dry, this pit can not step on it. Small white can not touch their own can be more learning communication group, there are big god can take you planning route.
1) Website backend programmer: use it to single site, background service is easier to maintain. Such as: Gmail, Youtube, Zhihu, Douban.
2) Automatic operation and maintenance: automatic processing of a large number of operation and maintenance tasks
3) Data analyst: rapid development and verification, analysis of data to obtain results
4) Game developers: It’s usually embedded in the game as a script
5) Automated tests: Write simple implementation scripts and apply them in Selenium/ LR to achieve automation.
6) Website development: Build my own website with Django and flask framework.
7) Crawler obtains or processes a large amount of information: download American TV series in batches, run investment strategies, climb suitable house sources, script tasks of system administrators, etc.
8) Artificial intelligence: Python is regarded as the main development language of artificial intelligence due to its advantages of simplicity, library, readability and implanting, so learning Python is the best way to enter the artificial intelligence industry.
Once I have determined the direction, the next step is to follow this direction and set up my own study plan.
Python learning plan (click to receive) Code: 166
This path is the logical main line of our systematic learning. According to the main line, I will decide what the next goal is to be completed and which knowledge points need to be learned, avoiding knowledge points that do not need to be learned temporarily. Then I can have some actual results for each part I learn, and use the results to form positive stimulation and stimulate the subsequent learning.
We in the follow-up learning process, master the basic knowledge, followed by the application, in the “use of in-depth understanding, in the in-depth understanding of the application of optimization”. Mutual verification and understanding is a natural process of deep learning. In addition, it is very easy to encounter programming error how to do? How to solve it?
The first step:
Encountered a lot of beginners, the environment will not install, guide package error, directly stuck to the first step, the result because of a very simple problem, but also wasted a lot of time, in fact, inside the god simple guidance can be suddenly enlightened, added the learning group of adorable new everyone must ask more and more communication.
The second step:
Really sorry to ask again about his baidu, refer to related articles, usually you meet problems, more than 90% have been met, baidu once, look at last some solutions, to try, be sure to consciously cultivate the ability to solve problems by themselves, which I think is do a basic literacy development.
Speaking of subconsciously developing your programming mind, let me give you a simple example. I have a list [1, 3,5,7,9] and I want to randomly select 3 elements. Is there the easiest way? When I encountered this, I consciously wanted to find out if there was a method in Python that could solve this problem with one line of code. As a result, I did find the sample method and used this line of code to solve this problem
In addition, there is a random sampling method for pandas DataFrame. In my work, I will search for random sampling methods for pandas DataFrame. A sample method was also found and sampled successfully
Step 3:
Baidu is less than, if it is some function, such as the programming method to consult relevant documents, look have a similar approach, such as the above data analysis library pandas random sampling sample usage, can be directly check out the official document, and see what is the use of the specification, such as, arrow, provided the number and proportion of two extraction ways, In this way, learning will progress.
Article reprinted: Le Byte