Among many programming languages, nothing seems to be able to stop Python. This month, Python ranked first again, with a market share of 13.42%. In 2023, Python has topped the list for 7 consecutive months, far ahead of other opponents.
After the list is released every month, some friends will be curious, why is it Python again? Why must you learn Python? In response to your two major questions, let’s talk about it below...
The first big question
Why is Python so popular?
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Easy to learn: Python is extremely easy to get started because Python has an extremely simple syntax.
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Rich resources: The Python standard library is huge and can help with various tasks. Many times, a few concise lines of code can solve a problem, greatly improving development efficiency.
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Wide application: Python is easy to learn, concise and rich in resources, making it widely used in different fields. Strong data processing capabilities can easily convert tedious and messy data into structured data, so that Python has become the most popular language in the field of big data.
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Cross-platform: Python is a scripting language that does not require compilation. Its execution is only related to the interpreter and has nothing to do with the operating system. The same code can run on different operating systems without modification.
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Extensible: Python is called the "glue" language. Python can be embedded into C/C++ programs to provide scripting functions to program users.
In summary, as an unrestricted, cross-platform open source programming language, Python is easy to learn, fast in data processing, powerful, and has a wide range of applications.
Therefore, it is not surprising that Python can remain number one for a long time. There is no doubt that Python has become an essential development language in many industries.
The second biggest question
Why must you learn Python?
It is better to take a look at the recruitment information and search for Python-related positions on third-party websites. You can see that the average monthly salary of Python development engineers in Beijing is 23.2K, of which 20K-30K accounts for the largest proportion.
In the same position, those with Python skills will have relatively higher salaries. After learning Python, the job prospects are very good, and promotions will be faster.
Currently, many students are studying Python+big data development courses. Although everyone has different starting points, they have gained something after studying and have realized their IT career dreams!
We all know that success is never achieved overnight. Only by calming down to study and accumulating strength over time can we be able to achieve success from the lowest point.
At present, the integration of digital technology and the real economy is accelerating, and digital technologies such as the Internet, big data, artificial intelligence, and cloud computing are accelerating. Python has become the darling of the times. Come and learn to "recharge" and give yourself a chance to "take off"!
Detailed introduction to Python+big data learning roadmap
Introduction to the first phase of big data development
Pre-study introduction: Start with traditional relational databases, master data migration tools, BI data visualization tools, and SQL to lay a solid foundation for subsequent learning.
1. Big data data development basics MySQL8.0 from entry to proficiency
MySQL is the entire IT basic course, and SQL runs through the entire IT life. As the saying goes, if you write SQL well, you can find a job easily. This course comprehensively explains MySQL8.0 from zero to advanced level. After studying this course, you can have the SQL level required for basic development.
The second stage of big data core foundation
Pre-study introduction: Learn Linux, Hadoop, Hive, and master the basic technologies of big data.
The 2022 version of Big Data Hadoop Introductory Tutorial
Hadoop Offline is the core and cornerstone of the big data ecosystem. It is an introduction to the entire big data development and a course that lays a solid foundation for later Spark and Flink. After mastering the three parts of the course: Linux, Hadoop, and Hive, you can independently implement visual report development for offline data analysis based on the data warehouse.
The third stage of hundreds of billions of data warehouse technology
Pre-study introduction: This stage of the course is driven by real projects and learns offline data warehouse technology.
Data offline data warehouse, enterprise-level online education project practice (complete process of Hive data warehouse project)
This course will establish a group data warehouse, unify the group data center, and centrally store and process scattered business data; the purpose is from demand research, design, Version control, research and development, testing to implementation, covering the complete process of the project; mining and analyzing massive user behavior data, customizing multi-dimensional data collections, and forming a data mart for use in various scene themes.
Phase 4 PB Memory Computing
Pre-study introduction: Spark has officially adopted Python as the first language on its homepage. In the update to version 3.2, it is highlighted that Pandas is built-in and bundled; the course fully complies with the trend of the technical community and recruitment needs, and is the first company in the entire network to add Python on Spark content.
1. Python from beginner to proficient (19 days complete)
Python basic learning course, starting from setting up the environment. Judgment statements, then basic data types, then learn and master functions, become familiar with file operations, initially build object-oriented programming ideas, and finally lead students into the Python programming palace with a case.
2.Advanced python programming from scratch to building a website
After studying this course, you will master Python's advanced syntax, multi-task programming and network programming.
3.spark3.2 from basics to mastery
Spark is the star product of the big data system. It is a high-performance distributed memory iterative computing framework that can process massive amounts of data. This course is developed based on Python language learning Spark3.2. The explanation of the course focuses on connecting theory with practice, is efficient and fast, and explains the profound things in simple terms, so that even beginners can master it quickly. Let experienced engineers also gain something.
4. Big data Hive+Spark offline data warehouse industrial project practice
Through the big data technology architecture, we solve the data storage and analysis, visualization, and personalized recommendation problems in the industrial Internet of Things manufacturing industry. The one-stop manufacturing project is mainly based on Hive data warehouse layering to store various business indicator data, and uses sparkSQL for data analysis. The core business involves operators, call centers, work orders, gas stations, and warehousing materials.