Are you wondering which programming language to learn first or how mastering a new one can advance your career? If so, consider Python, a flexible programming language with many uses throughout different industries. Python is used for traditional programming tasks, data analysis, and even AI development.
Discover why programmers and developers learn Python and explore its many applications.
Why is Python popular?
Guido van Rossum developed Python in 1989 to help programmers with their productivity. In 2025, Python's use goes far beyond Rossum's initial vision. The language's popularity stems from its ease of use and other benefits, including:
- Many built-in libraries
- Modern scripting and easy-to-read syntax
- Large community of passionate Python users
- Helpful how-to guides for coders learning on their own
- Open-source software
- Short setup time
- Application to web development, software development, and AI
These benefits make Python a great first language for computer science majors and professionals interested in learning coding.
What is Python used for?
Back-end web development
Many coders learn Python to work in back-end web development, a branch of web development focusing on the site architecture all websites need to function.
Back-end developers use Python for server-side scripting, software programs that generate outputs based on user inputs. Python also features Flask, an intuitive microweb framework that helps back-end developers create web applications.
Although essential, Python is not the only programming language back-end web developers need to know. Learn more about how to become a web developer.
Data analysis and visualization
Data analysis and visualization involve turning large data sets into usable charts and graphics. Programmers fluent in Python can easily:
- Import libraries
- Manipulate data
- Find correlations between numeric data
Python lets programmers customize how they want to present their findings. This advantage lets you custom-tailor your visualizations to your target audience and highlight the most important information. You can learn more about Python's role in data analysis and data visualization by exploring top courses and degrees on edX.
Machine learning
Programmers that specialize in machine learning create AI software that can learn and act independently. They use Python and other programming languages to develop the statistical models and algorithms AI software needs to make predictions based on large data sets. Python can also help programmers:
- Develop effective algorithms
- Analyze AI model performance
- Make adjustments for optimization
Machine learning courses can teach you more about the field's fundamentals and real-world applications. Consider taking these courses alongside Python courses to learn how they complement one another.
Software development
Although you can develop software using many programming languages, Python stands apart for its simplicity and accessibility. Its code libraries and frameworks let you easily create, test, and troubleshoot new software. Python's data visualization tools also make it a great choice for seeing how software will look and work for end users.
These features make Python a good choice for students learning software development. Courses can help you master the techniques that development teams use when collaborating on the latest software suites.
Automation
Routine, repetitive tasks can make any job tedious and increase the chances of human error. You can use Python to automate many processes, including:
- File handling
- Error handling
- Parsing
- Command line weaving
- Batch processing
- Spatial analysis
- Data management
The benefits of learning automation with Python go further than saving you time. Automation skills can make you desirable to employers in many fields, such as logistics, manufacturing, finance, and information technology.
Web scraping
The Python libraries BeautifulSoup and Selenium help coders scrape data from millions of websites. Coders can tell these libraries to explore websites across different browsers and parse relevant information with just a few keystrokes. The libraries can then compile and organize this data into one convenient file.
Large language models and other AI programs train on the data sets that web scraping produces. Learning Python for web scraping can make you a competitive job applicant in this emerging field.