Python is liked and learned by more and more people. The following is the learning route of python, which is very suitable for beginners to learn.
Python language basics
(1) Introduction to Python3, data types, strings
(2) Judgment/loop statements, functions, namespaces , Scope
(3) Classes and objects, inheritance, polymorphism
(4) Tkinter interface programming
(5) Files and exceptions, introduction to data processing
(6) Pygame actual aircraft battle, 2048
Python language advanced
(1) Python common third-party libraries and network programming
(2) Python regular expression
(3) Mailbox crawler, file traversal, financial data crawler, multi-threaded crawler
(4) Python thread and process
(5) Python MySQL database, coroutine, jython
python full stack engineer front-end
(1) HTML
( 2) HTML5
(3) CSS
(4) CSS3
(5) Web interface design practice
(6) javaScript
(7) jquerry
(8) jquerry EasyUI, Mobile introduction, photoshop
(9) Bootstrap
python full stack engineer backend
(1) Getting started with Django
(2) Advanced Django
(3) Practical Django
Python full stack engineer backend advanced
(1) Flask development principles
(2) Flask development project practice
(3) Tornado development principles
(4) Tornado development Project practice
Linux basics
(1) File processing commands
(2) Permission management commands
(3) Help command
(4) File search command
(5) Compression and decompression command
(6) Command usage skills
( 7) VIM usage
(8) Software package management
(9) User and user group management
(10) Linux Shell development
Linux operation and maintenance automation development
(1) Python development Linux operation and maintenance
(2) Linux operation and maintenance alarm tool development
(3) Linux operation and maintenance alarm security audit development
(4) Linux business quality report tool development
(5) Kali security detection tool detection
(6) Kali password cracking practice
python data analysis
(1) numpy data processing
(2) pandas data analysis
(3) matplotlib data visualization
(4) scipy data statistical analysis
(5) python financial data analysis
python big data
(1) Hadoop HDFS
(2) python Hadoop MapReduce
(3) python Spark core
(4) python Spark SQL
(5) python Spark MLlib
python machine learning
(1) Introduction to basic knowledge of machine learning
(2) KNN algorithm
(3) Linear regression
(4) Logistic regression algorithm
(5) Decision tree algorithm
(6) Naive Bayes algorithm
(7) Support vector machine
(8) Clustering k-means algorithm
The above is the detailed content of python learning route. For more information, please follow other related articles on the PHP Chinese website!

Python and C each have their own advantages, and the choice should be based on project requirements. 1) Python is suitable for rapid development and data processing due to its concise syntax and dynamic typing. 2)C is suitable for high performance and system programming due to its static typing and manual memory management.

Choosing Python or C depends on project requirements: 1) If you need rapid development, data processing and prototype design, choose Python; 2) If you need high performance, low latency and close hardware control, choose C.

By investing 2 hours of Python learning every day, you can effectively improve your programming skills. 1. Learn new knowledge: read documents or watch tutorials. 2. Practice: Write code and complete exercises. 3. Review: Consolidate the content you have learned. 4. Project practice: Apply what you have learned in actual projects. Such a structured learning plan can help you systematically master Python and achieve career goals.

Methods to learn Python efficiently within two hours include: 1. Review the basic knowledge and ensure that you are familiar with Python installation and basic syntax; 2. Understand the core concepts of Python, such as variables, lists, functions, etc.; 3. Master basic and advanced usage by using examples; 4. Learn common errors and debugging techniques; 5. Apply performance optimization and best practices, such as using list comprehensions and following the PEP8 style guide.

Python is suitable for beginners and data science, and C is suitable for system programming and game development. 1. Python is simple and easy to use, suitable for data science and web development. 2.C provides high performance and control, suitable for game development and system programming. The choice should be based on project needs and personal interests.

Python is more suitable for data science and rapid development, while C is more suitable for high performance and system programming. 1. Python syntax is concise and easy to learn, suitable for data processing and scientific computing. 2.C has complex syntax but excellent performance and is often used in game development and system programming.

It is feasible to invest two hours a day to learn Python. 1. Learn new knowledge: Learn new concepts in one hour, such as lists and dictionaries. 2. Practice and exercises: Use one hour to perform programming exercises, such as writing small programs. Through reasonable planning and perseverance, you can master the core concepts of Python in a short time.

Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.


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