What Is Python Used For? A Beginner’s Guide
Python is one of the most widely used programming languages. Learn more about how its used for everything from machine learning to building websites and software testing.
![[Featured image] A software developer coding in Python on her laptop.](https://d3njjcbhbojbot.cloudfront.net/api/utilities/v1/imageproxy/https://images.ctfassets.net/wp1lcwdav1p1/NMcuhoa0Wv2onqR1dHsdv/bc44ad70d277a30f295964e414a8339c/iStock-964372340.jpg?w=1500&h=680&q=60&fit=fill&f=faces&fm=jpg&fl=progressive&auto=format%2Ccompress&dpr=1&w=1000)
Python, one of the most popular programming languages in the world, has created everything from Netflix’s recommendation algorithm to the software that controls self-driving cars. Python is a general-purpose language, which means it’s designed to be used in a range of applications, including data science, software and web development, automation, and generally getting stuff done.
In this article, you'll learn more about what Python is and how it's used in the real world. If you want to start learning this popular programming language today, consider enrolling in the University of Michigan's Python for Everybody Specialization where you'll build foundational programming knowledge in as little as two months.
specialization
Python for Everybody
Learn to Program and Analyze Data with Python. Develop programs to gather, clean, analyze, and visualize data.
4.8
Beginner level
Average time: 2 month(s)
Learn at your own pace
Skills you'll build:
Data Structures, Database Systems, Database Design, Application Programming Interface (API), SQL, Python Programming, Programming Principles, Data Collection, Web Services, Web Scraping, Databases, Restful API, JSON, Relational Databases, Database Management, Data Visualization, Network Protocols, Computer Programming, Data Processing, Data Modeling, File Management, Data Import/Export, Development Environment, Data Manipulation, Data Visualization Software, Object Oriented Programming (OOP), Exploratory Data Analysis, Unstructured Data, Algorithms, Data Analysis, Software Installation, Extensible Markup Language (XML), Hypertext Markup Language (HTML), TCP/IP, Data Access, Data Capture, Text Mining, Scripting
What is Python?
Python is a computer programming language often used to build websites and software, automate tasks, and conduct data analysis. Python is a general-purpose language, meaning it can be used to create a variety of different programs and isn’t specialized for any specific problems. This versatility, along with its beginner-friendliness, has made it one of the most-used programming languages today.
According to a study by Statista, Python is the third most commonly used programming language among developers worldwide [1].
Did you know? The name Python comes from Monty Python. When Guido van Rossum was creating Python, he was also reading the scripts from BBC’s Monty Python’s Flying Circus. He thought the name Python was appropriately short and slightly mysterious.
What is Python used for?
Python is commonly used for developing websites and software, task automation, data analysis, and data visualization. Since it’s relatively easy to learn, Python has been adopted by many non-programmers, such as accountants and scientists, for a variety of everyday tasks, like organizing finances.
“Writing programs is a very creative and rewarding activity,” says University of Michigan and Coursera instructor Charles R Severance in his book Python for Everybody. “You can write programs for many reasons, ranging from making your living to solving a difficult data analysis problem to having fun to helping someone else solve a problem.”
What can you do with Python? Some things include:
Data analysis and machine learning
Web development
Automation or scripting
Software testing and prototyping
Everyday tasks
Here’s a closer look at some of these common ways Python is used.
1. Data analysis and machine learning
Python has become a staple in data science, allowing data analysts and other professionals to use the language to conduct complex statistical calculations, create data visualizations, build machine learning algorithms, manipulate and analyze data, and complete other data-related tasks.
Python can build a wide range of different data visualizations, like line and bar graphs, pie charts, histograms, and 3D plots. Python also has a number of libraries that enable coders to write programs for data analysis and machine learning more quickly and efficiently, like TensorFlow and Keras.
professional certificate
Google Advanced Data Analytics
Learn in-demand skills like statistical analysis, Python, regression models, and machine learning in less than 6 months.
4.8
Advanced level
Average time: 6 month(s)
Learn at your own pace
Skills you'll build:
Tableau Software, Exploratory Data Analysis, Regression Analysis, Machine Learning, Sampling (Statistics), Object Oriented Programming (OOP), Python Programming, Descriptive Statistics, Data Ethics, Statistical Hypothesis Testing, Feature Engineering, Data Analysis, Interviewing Skills, Data Visualization, Statistical Analysis, Data Storytelling, Data Visualization Software, Data Science, Data Presentation, Advanced Analytics, Business Analysis, Machine Learning Methods, Artificial Intelligence, Project Portfolio Management, Predictive Modeling, Statistical Modeling, Variance Analysis, Scikit Learn (Machine Learning Library), Analytical Skills, Probability & Statistics, Correlation Analysis, Business Analytics, Supervised Learning, NumPy, Programming Principles, Pandas (Python Package), Scripting, Data Structures, Algorithms, Data Manipulation, Communication, Project Management, Workflow Management, Stakeholder Communications, Data-Driven Decision-Making, Unsupervised Learning, Random Forest Algorithm, Machine Learning Algorithms, Decision Tree Learning, Performance Metric, Performance Tuning, Classification And Regression Tree (CART), Generative AI, Personal Attributes, Applicant Tracking Systems, Professional Development, Statistical Inference, Statistics, A/B Testing, Probability Distribution, Probability, Statistical Methods, Statistical Programming, Technical Communication, Data Cleansing, Data Validation, Data Processing, Data Transformation, Data Quality
2. Web development
Python is often used to develop the back end of a website or application—the parts that a user doesn’t see. Python’s role in web development can include sending data to and from servers, processing data and communicating with databases, URL routing, and ensuring security. Python offers several frameworks for web development. Commonly used ones include Django and Flask.
Some web development jobs that use Python include back-end engineers, full-stack engineers, Python developers, software engineers, and DevOps engineers.
Read more: How to Become a Web Developer
professional certificate
Meta Back-End Developer
Launch your career as a back-end developer. Build job-ready skills for an in-demand career and earn a credential from Meta. No degree or prior experience required to get started.
4.7
Beginner level
Average time: 8 month(s)
Learn at your own pace
Skills you'll build:
Full-Stack Web Development, Cloud Hosting, Data Structures, Web Design and Development, Front-End Web Development, Database Design, SQL, Object Oriented Programming (OOP), Unix Commands, Python Programming, GitHub, Database Management Systems, Restful API, Git (Version Control System), Relational Databases, Version Control, Back-End Web Development, Computer Programming, Bootstrap (Front-End Framework), Django (Web Framework), Unit Testing, MySQL, Databases, Server Side, API Design, Software Testing, Application Development, User Accounts, Web Applications, Data Validation, Authentications, Debugging, Application Programming Interface (API), Authorization (Computing), Software Documentation, Performance Tuning, JSON, Test Tools, Extensible Markup Language (XML), Database Administration, NoSQL, Query Languages, Javascript, Cascading Style Sheets (CSS), Hypertext Markup Language (HTML), Cloud Computing, Scalability, Virtual Environment, Responsive Web Design, Web Development, Data Modeling, Application Frameworks, Database Development, Application Security, Web Servers, Database Management, Algorithms, Technical Communication, Computer Science, Pseudocode, Program Development, Software Visualization, Computational Thinking, Communication, Programming Principles, Computational Logic, Test Driven Development (TDD), Development Environment, Integrated Development Environments, Linux Commands, Software Versioning, Software Development Tools, Software Development, File Management, Command-Line Interface, Linux, Collaborative Software, React.js, HTML and CSS, JavaScript Frameworks, General Networking, User Interface (UI)
3. Software testing and prototyping
In software development, Python can aid in tasks like build control, bug tracking, and testing. With Python, software developers can automate testing for new products or features. Some Python tools used for software testing include Green and Requestium.
4. Automation or scripting
If you find yourself performing a task repeatedly, you could work more efficiently by automating it with Python. Writing code used to build these automated processes is called scripting. In the coding world, automation can be used to check for errors across multiple files, convert files, execute simple math, and remove duplicates in data.
Python can even be used by relative beginners to automate simple computer tasks—such as renaming files, finding and downloading online content, or sending emails or texts at desired intervals.
IT automation can be a valuable skill to add to your resume. You can learn the basics from an industry leader in technology with the following online program:
professional certificate
Google IT Automation with Python
Learn in-demand skills like Python, Git, and IT automation to advance your career
4.8
Advanced level
Average time: 6 month(s)
Learn at your own pace
Skills you'll build:
Automation, Unit Testing, Technical Communication, Configuration Management, Debugging, Cloud Computing, Applicant Tracking Systems, Scripting, Python Programming, Puppet (Configuration Management Tool), Programming Principles, GitHub, Bash (Scripting Language), Web Services, CI/CD, Cloud Services, Git (Version Control System), Infrastructure as Code (IaC), Version Control, Interviewing Skills, Operating Systems, File Management, Linux Commands, Test Driven Development (TDD), Development Environment, Unix Commands, Unix, Scripting Languages, Command-Line Interface, Shell Script, OS Process Management, Unix Shell, Scalability, Cloud Storage, Load Balancing, Containerization, Infrastructure Architecture, DevOps, System Monitoring, Kubernetes, Docker (Software), Continuous Integration, Code Review, Software Versioning, Software Development Tools, Software Engineering Tools, Issue Tracking, Communication, Generative AI, Personal Attributes, Professional Development, Performance Tuning, Application Performance Management, Incident Management, Problem Management, System Support, Technical Documentation, Network Troubleshooting, Technical Support, Data Structures, Algorithms, Computer Programming, Integrated Development Environments, Computational Thinking, Application Programming Interface (API), Restful API, Maintainability, Image Analysis, JSON
5. Everyday tasks
Python isn't only for programmers and data scientists. Learning Python can open new possibilities for those in less data-heavy professions, like journalists, small business owners, or social media marketers. Python can also enable non-programmers to simplify certain tasks in their lives. Here are just a few of the tasks you could automate with Python:
Keep track of stock market or crypto prices
Send yourself a text reminder to carry an umbrella anytime it’s raining
Update your grocery shopping list
Renaming large batches of files
Converting text files to spreadsheets
Randomly assign chores to family members
Fill out online forms automatically
Subscribe to our weekly newsletter Career Chat. It's a low-commitment way to stay current with industry trends and skills you can use to guide your career path.
Why is Python so popular?
Python is popular for a number of reasons. Here’s a deeper look at what makes it so versatile and easy to use for coders.
Its simple syntax mimics natural language, making it easier to read and understand. This makes it quicker to build projects and improve on them.
It’s versatile. Python can be used for many different tasks, from web development to machine learning.
It’s beginner-friendly, making it popular for entry-level coders.
It’s open source, which means it’s free to use and distribute, even for commercial purposes.
Python’s archive of modules and libraries—bundles of code that third-party users have created to expand Python’s capabilities—is vast and growing.
Python has a large and active community that contributes to Python’s pool of modules and libraries, and acts as a helpful resource for other programmers. The vast support community means that if coders run into a stumbling block, finding a solution is relatively easy; somebody is bound to have encountered the same problem before.
Practice your Python skills independently with tutorials
Not ready to commit to a course or a boot camp yet? You can read step-by-step guides for troubleshooting Python basics like syntax, if-else statements, exceptions, and working with loops in Coursera's free programming tutorials.
Learn Python today on Coursera
There are several online courses available to start learning or continue building your Python skills.
Explore the basics with Duke University's Python Programming Fundamentals course. In less than 23 hours, you'll learn conditionals, loops, mathematical operators, and data types, and then will develop a Python Program from scratch.
Build your skills with the University of Michigan's Python for Everybody Specialization. Over five courses, you'll go deeper into data structures, accessing web data, and using databases, culminating in a hands-on project to create your own applications for data retrieval, processing, and visualization.
Develop machine learning models with DeepLearning.AI's Deep Learning Specialization. Through five courses, you'll learn theoretical concepts along with how to use Python and Tensorflow to tackle real-world cases like speech recognition, chatbots, and machine translation.
specialization
Python for Everybody
Learn to Program and Analyze Data with Python. Develop programs to gather, clean, analyze, and visualize data.
4.8
Beginner level
Average time: 2 month(s)
Learn at your own pace
Skills you'll build:
Data Structures, Database Systems, Database Design, Application Programming Interface (API), SQL, Python Programming, Programming Principles, Data Collection, Web Services, Web Scraping, Databases, Restful API, JSON, Relational Databases, Database Management, Data Visualization, Network Protocols, Computer Programming, Data Processing, Data Modeling, File Management, Data Import/Export, Development Environment, Data Manipulation, Data Visualization Software, Object Oriented Programming (OOP), Exploratory Data Analysis, Unstructured Data, Algorithms, Data Analysis, Software Installation, Extensible Markup Language (XML), Hypertext Markup Language (HTML), TCP/IP, Data Access, Data Capture, Text Mining, Scripting
specialization
Deep Learning
Become a Machine Learning expert. Master the fundamentals of deep learning and break into AI. Recently updated with cutting-edge techniques!
4.9
Intermediate level
Average time: 3 month(s)
Learn at your own pace
Skills you'll build:
Artificial Neural Networks, Natural Language Processing, PyTorch (Machine Learning Library), Debugging, Tensorflow, Machine Learning, Artificial Intelligence, Applied Machine Learning, Performance Tuning, Python Programming, Deep Learning, Keras (Neural Network Library), Linear Algebra, Computer Vision, Machine Learning Algorithms, Large Language Modeling, Image Analysis, Supervised Learning, Artificial Intelligence and Machine Learning (AI/ML), Analysis, Data Quality, Application Frameworks, Calculus, Algorithms, Data Processing
Frequently asked questions (FAQ)
Article sources
Statista. "Most used programming languages among developers worldwide as of 2024, https://www.statista.com/statistics/793628/worldwide-developer-survey-most-used-languages/." Accessed January 21, 2025.
Coursera Staff
Editorial Team
Coursera’s editorial team is comprised of highly experienced professional editors, writers, and fact...
This content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.