In general, it takes around two to six months to learn the fundamentals of Python. But you can learn enough to write your first short program in a matter of minutes. Developing mastery of Python’s vast array of libraries can take months or years.
How long it takes you to learn Python will depend on several factors, including how much Python you need to know to achieve your desired goal. If you want to learn enough Python to automate a specific task at work, for example, you can likely achieve that more quickly than if you wanted to learn enough Python to get a job as a data analyst. Here are some other factors that can influence how quickly you pick up Python:
Previous programming experience: If you’ve written code before, you may find that you pick up Python more quickly.
Learning method: Well-structured courses in line with your goals can sometimes accelerate your learning.
Time devoted to learning: How much time can you devote to learning and practicing Python? Generally, it’s a good idea to commit a little time every day.
Ready to start learning? If you’re not quite sure how Python fits with your personal and professional goals, consider a broad introductory course, like Python for Everybody. If, on the other hand, you’d like to develop your Python skills for a career as a data analyst, consider earning the IBM Data Analyst Professional Certificate. You’ll get hands-on experience working with Python, as well as SQL, Excel, and Jupyter notebooks.
It’s possible to learn the basics of Python in two to six months, though this could be much more or much less depending on how much time you dedicate to learning. The Python for Everybody Specialization on Coursera, for example, typically takes about four months to complete if you’re spending six hours per week on the courses. If you can dedicate more time, let’s say two hours per day, you could complete the Specialization in two months.
In this and many other introductory courses, you might expect to learn the following foundational syntax and elements of Python:
Variables and types
Object and data structures (strings, integers, floats, etc.)
Indexing and slicing
For and while loops
Lists, dictionaries, and tuples
Reading and writing to files
Classes and objects
Application programming interfaces (APIs)
Once you’ve built a foundational knowledge of Python, you can begin progressing your programming skills toward your own unique goals, whether it be a job as a data analyst or application developer or the ability to automate tasks at work.
This depends on what mastery means to you.
There are some 8.2 million Python developers in the world, according to developer analyst company SlashData . With so many people working on this open-source software, it’s always evolving to include new tools and capabilities. You’ll never know everything there is to know about Python, and that’s okay.
Python users have access to tens (if not hundreds) of thousands of libraries—sets of useful functions meant to make coding easier. TensorFlower, for example, can help streamline machine learning programs, while Pandas offers access to flexible and responsive data structures. This means that mastering Python is an ongoing process where you learn what you need to know as you need it.
Python is widely considered among the easiest programming languages for beginners to learn. If you’re interested in learning a programming language, Python is a good place to start. It’s also one of the most widely used. The TIOBE Index for June 2021 lists Python as the second most popular language after C, and its popularity is growing . As you learn, you can take advantage of the robust community of fellow learners and developers, as well as the job opportunities that come with knowing Python.
Python is also very versatile. Since it’s a general purpose language, Python can be used for a variety of tasks, including:
Task automation or scripting
Web and software development
Python ranks among the world’s most popular programming languages in part because it’s used across a variety of industries and job roles. By learning to write Python, you can create opportunities for a variety of careers. Some job titles that use Python include:
Data analyst - $68,583
Backend developer - $78,585
Quality assurance engineer - $85,731
Operations automation engineer - $88,462
Python developer - $95,849
Full stack developer - $99,106
Data engineer - $112,071
Data scientist - $116,041
Machine learning engineer - $129,417
*Salary data represents US average in June 2021 from Glassdoor
While learning a technical skill like programming with Python may sound intimidating, it may not be as difficult as you think. Keep these tips to enhance your learning.
Python is a language, and just like any other language, repetition is key to learning it. Dedicate time everyday—even if it’s just 15 minutes—to practice coding. Many online Python courses, including Python for Everybody, are broken up into short video lectures, quizzes, and coding practice exercises. This type of structure can make it easier to find time to learn into your life.
It may also help you learn more efficiently. Learning in small chunks, a technique known as microlearning, improves retention and engagement.
No matter how you plan to use Python in the future, you’ll want to start with the same set of fundamentals. Learning the basics first will set you up for success when you go on to tackle more complex uses. Whether you’re learning on your own or through a course, be sure to cover the fundamentals listed above (See “How long does it take to learn basic Python?”).
Understanding the how and the why of your lines of code in Python is more important than memorizing the syntax.
Remembering to close your parentheses or include a colon before an indent will come with repetition. Plus, you can always look up how to structure your code on Google or Stack Overflow (an online community for programmers). But you’ll need to understand the logic of what you’re trying to accomplish.
As you’re working through Python coding problems, you may find it helpful to hand write an outline of what your code needs to do without worrying about syntax. This is called pseudocode—a technique even experienced Python programmers use to plan out their programs.
Once you’ve built a foundation with the basics, the world of Python really opens up. As you progress, it’s important to know your goal and let it dictate your learning path.
If you’re building the skills for a new career as a data analyst, for example, you’ll probably want to learn Python skills like data scraping or visualization. If you’re more interested in becoming a developer, you may focus on skills like version control and multi-process architecture.
The types of libraries, frameworks, and the integrated development environment (IDE) you learn to work with will also vary based on your career goals.
Instead of learning to code as a solitary activity, surround yourself (virtually, anyway) with others who are learning Python. This can help boost your motivation while giving you a place to swap tips and tricks with other programmers.
Yes, it’s totally possible to teach yourself Python. You’ll find a variety of resources, from YouTube videos to books to interactive games, that can help you develop your coding skills. Many online courses also allow you to learn at your own pace, but with added structure, a clear learning path, and sometimes a built-in community of other learners.
Python is actually one of the best programming languages for beginners. Its syntax is similar to English, which makes it relatively easy to read and understand. With some time and dedication, you can learn to write Python, even if you’ve never written a line of code before.
It’s a common misconception that programming requires a lot of math. You don’t have to be a math whiz to succeed with Python. It helps to have a basic understanding of arithmetic. Writing Python is more about being able to solve problems by breaking them down into smaller steps, then using your creativity to craft a solution.
Unless you have a very specific reason for using Python 2, you should be using Python 3. Most companies use Python 3, plus Python 2 was sunsetted on January 1, 2020. This means that no more features, fixes, or security updates will be added.
Python is a valuable skill to have on your resume, but most jobs require a set of skills. If you’re going into data analytics, for example, you’ll likely need to have some proficiency in SQL, statistics, and data visualization. Developers may need to understand data structures, network basics, and testing methods.
Start learning Python alongside a host of other data analytics skills with the IBM Data Analyst Professional Certificate on Coursera. You can build job-ready skills in less than six months and finish with a credential for your resume from an industry leader.
1. SlashData. "Global developer population report, https://slashdata-website-cms.s3.amazonaws.com/sample_reports/EiWEyM5bfZe1Kug_.pdf." Accessed June 23, 2021.
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.