What is Python? What is the current situation of Python talent demand? How to learn programming?

foreword

Python is a high-level programming language. Its design emphasizes the readability and simplicity of code, making Python a scripting language with clear writing, strong logic, and less code. At the same time, Python is also an interpreted language that can run on cross-platform (such as Windows, MacOS and various Linux distributions) operating systems. Python has a wide range of applications, including Web development, network programming, data analysis, artificial intelligence and other fields.

Python is like a Swiss army knife, full-featured, easy to use, and will automatically complain about your typos, so that you can feel a touch of human care even when you are talking to the machine.

Current status of Python talent demand

Python is currently very hot and is one of the most widely used programming languages ​​in the world. The survey results show that Python currently has strong demand and applications in many fields, including web development, data science, artificial intelligence, machine learning, natural language processing, and more. Many companies and organizations are actively recruiting Python development talents, so Python developers are currently in high demand.

According to the latest recruitment statistics, Python is currently very popular in the industry, and the salary of Python engineers has exceeded that of engineers in many other programming languages.

[----Help Python learning, all the following learning materials are free at the end of the article! ----】

1. Artificial Intelligence and Machine Learning: This is one of the most urgent areas for Python talent right now. Many companies are looking for Python engineers who can develop and maintain artificial intelligence systems, including machine learning, deep learning, data mining, natural language processing and other technical fields.

2. Web frameworks and web development: Python has many popular web frameworks, such as Django and Flask, so many companies and organizations need Python development talents to help them build and maintain web applications.

3. Data Science and Data Analysis: Python has many libraries and frameworks for data science and data analysis, such as Pandas, NumPy, and Matplotlib, etc. Therefore, Python is also promising for those companies and organizations that need to analyze large amounts of data and extract data insights.

4. Game development: Python can also be used for game development, mainly through Pygame. Although the application of Python in the field of game development is not very common, but with the continuous development and progress of Python, it is believed that more and more game developers will choose Python.

learn python

1. Understand the basics: You first need to learn the basics of Python, such as data types, operators, control flow, functions, and more. You can learn by reading Python's official documentation, reference books, or online tutorials.

2. Practical operation: Keep practicing during the learning process. It is best to install the Python environment on the computer and write some codes to practice, so that you can better understand and memorize the knowledge points.

3. Learning libraries and frameworks: In addition to learning the basics of Python, you also need to learn some popular Python libraries and frameworks, such as NumPy, Pandas, Matplotlib, Django, Flask, and more. These libraries and frameworks can help you complete some common tasks and projects more conveniently.

4. Participate in the community: Participating in Python community activities, such as participating in online/offline technology sharing sessions, contributing code, participating in Stack Overflow, etc., are very beneficial.

5. Continuous learning: Python is a programming language that is constantly being developed and updated, so keep up with the latest developments, learn about new libraries and frameworks in real time, and learn from other people's experiences and techniques.

Finally, I will introduce a complete python learning route, from entry to advanced, including mind maps, classic books, and supporting videos, to help those who want to learn python and data analysis!

How to use python, SQL and other tools are the tricks that need to be used in the data analysis process. And the necessary hard skills! !

1. Introduction to Python

The following content is the basic knowledge necessary for all application directions of Python. If you want to do crawlers, data analysis or artificial intelligence, you must learn them first. Anything tall is based on primitive foundations. With a solid foundation, the road ahead will be more stable.

Include:

Computer Basics

python basics

Python introductory video 600 episodes:

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.

2. Python crawler

As a popular direction, reptiles are a good choice whether it is a part-time job or as an auxiliary skill to improve work efficiency.

Relevant content can be collected through crawler technology, analyzed and deleted to get the information we really need.

This information collection, analysis and integration work can be applied in a wide range of fields. Whether it is life services, travel, financial investment, product market demand of various manufacturing industries, etc., crawler technology can be used to obtain more accurate and effective information. use.

Python crawler video material

3. Data Analysis

According to the report "Digital Transformation of China's Economy: Talents and Employment" released by the School of Economics and Management of Tsinghua University, the gap in data analysis talents is expected to reach 2.3 million in 2025.

With such a big talent gap, data analysis is like a vast blue ocean! A starting salary of 10K is really commonplace.

4. Database and ETL data warehouse

Enterprises need to regularly transfer cold data from the business database and store it in a warehouse dedicated to storing historical data. Each department can provide unified data services based on its own business characteristics. This warehouse is a data warehouse.

The traditional data warehouse integration processing architecture is ETL, using the capabilities of the ETL platform, E = extract data from the source database, L = clean the data (data that does not conform to the rules), transform (different dimension and different granularity of the table according to business needs) calculation of different business rules), T = load the processed tables to the data warehouse incrementally, in full, and at different times.

5. Machine Learning

Machine learning is to learn part of the computer data, and then predict and judge other data.

At its core, machine learning is "using algorithms to parse data, learn from it, and then make decisions or predictions about new data." That is to say, a computer uses the obtained data to obtain a certain model, and then uses this model to make predictions. This process is somewhat similar to the human learning process. For example, people can predict new problems after obtaining certain experience.

Machine Learning Materials:

6. Advanced Python

From basic grammatical content, to a lot of in-depth advanced knowledge points, to understand programming language design, after learning here, you basically understand all the knowledge points from python entry to advanced.

At this point, you can basically meet the employment requirements of the company. If you still don’t know where to find interview materials and resume templates, I have also compiled a copy for you. It can really be said to be a systematic learning route for nanny and .

But learning programming is not achieved overnight, but requires long-term persistence and training. In organizing this learning route, I hope to make progress together with everyone, and I can review some technical points myself. Whether you are a novice in programming or an experienced programmer who needs to be advanced, I believe that everyone can gain something from it.

It can be achieved overnight, but requires long-term persistence and training. In organizing this learning route, I hope to make progress together with everyone, and I can review some technical points myself. Whether you are a novice in programming or an experienced programmer who needs to be advanced, I believe that everyone can gain something from it.

Data collection

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