How to Learn Python: A Step-by-Step Guide for Beginners for 2025

Python is a programming language that powers much of today’s technology. Banks use it to detect fraud, researchers process medical data with it, and developers build web applications.

The good news?  Python’s clean syntax and approachable design make it easy to learn, even without coding experience.

In this guide, we’ll share everything you need to know about Python—how to find useful resources, learn it fast, and land a job.

What is Python?

Python is a high-level programming language, meaning it handles various complex computer tasks automatically. 

It’s also interpreted—the code runs line by line, making it easier to test and debug than languages like C++ or Java.

Wondering what you can do with Python? Almost anything. For instance:

• Analyze massive amounts of data to predict sales or spot fraud
• Power web development projects, from websites to complex apps 
• Build AI systems that recognize images or answer questions
• Create games and desktop applications
• Automate tasks like processing thousands of files

Companies use code like this all the time to check if email addresses are real, pull important data from documents, or spot spam emails.

Should you Learn Python in 2025?

Short answer: Yes. 

There’s a lot of demand for Python, with the TIOBE Index ranking it as the top programming language. Its adoption has grown by about 50% in recent years, and we expect this trend to continue.

Prestigious companies like Google, Facebook, Amazon, NASA, and many others use Python for various applications. It’s also extremely popular among tech startups of all kinds.

So, if you’re considering learning a programming language, Python is a safe bet for career prospects. It can also be useful for other professions, including marketing, business analytics, etc.

Key benefits of learning Python:

• Career opportunities: Python skills open doors to many lucrative and in-demand careers in technology, finance, healthcare, and more.
• Versatility: Python’s applicability spans web development, data analysis, automation, machine learning, and numerous other domains.
• Ease of learning: Python’s clear and concise syntax makes it one of the most beginner-friendly programming languages.
• Community and resources: It has a large and supportive community with various online tutorials, courses, and documentation.
• Future-proofing: Python continues to grow in popularity and expand into new fields like AI and machine learning. Which means it’s most likely to stay relevant for years to come.

How Long Does it Take to Learn Python?

The timeline to learn Python varies widely, depending on your goals and prior programming experience. Here’s what it might look like if you’re learning consistently (at least 5-10 hours per week).

Learning the basics:

• A few weeks: With focused effort, you can learn the basic Python syntax, data types, and operations in a few weeks.
• 1-3 months: This is a more typical timeframe for gaining a grasp of the core concepts and being able to write simple programs.

Becoming proficient:

• 6-12 months: It can take several months of consistent practice and learning to become comfortable with Python’s more advanced features, libraries, and frameworks.
• Ongoing learning: Python is a vast language with numerous libraries and applications. Mastering it means staying up-to-date with all recent changes and developments.  

Python vs. other languages: time to learn

• Python is often considered one of the easiest languages to learn. Acquiring basic knowledge takes 1-3 months.
• Java: More complex due to its syntax and concepts like memory management and multithreading. Learning Java can take longer, with basic proficiency achieved in about 3-6 months and advanced proficiency in 1-2 years.
• JavaScript: The learning curve for basic JavaScript syntax is similar to Python. However, understanding its use in web development, including frameworks like React or Angular, can extend the timeline to 6-12 months for basic mastery.
• C++: Known for its complexity and steep learning curve, basic C++ proficiency can take six months, with advanced mastery requiring 1-2 years.
• Ruby: You can master the basics in 1-3 months. Intermediate to advanced proficiency can take 6-12 months, particularly for web development with Ruby on Rails.

How to Learn Python in 7 Steps

Follow these practical steps to begin your Python learning journey: 

1. List your goals for learning Python

Before you even write a line of Python code, take some time to define your learning goals. This will help you move faster, focus on what matters, and stay motivated. Ask yourself these questions:

• Why do I want to learn Python? Are you looking to switch careers, automate work tasks, build a personal project, or simply expand your knowledge?
• What do I want to build or achieve with Python? Do you dream of creating web applications, analyzing big data, or diving into machine learning? Or you may want to automate some marketing analytics tasks.
• How much time am I willing to dedicate to learning Python? Be realistic about your schedule and set achievable milestones.

Remember, your goals can be as specific or broad as you want and may change over time. The key is to have a clear direction to guide your learning journey.

2. Choose your learning method

The good news is you don’t need a computer science degree to become proficient in Python. There are two main learning approaches you can take from the comfort of your home: 

Self-learning

This involves independently using various resources to learn Python at your own pace. It’s flexible, often free or low-cost, and allows you to tailor your learning experiences to your specific interests and schedule. 

Self-learning resources to get you started: 

• Online tutorials and interactive forums: W3schools, FreeCodeCamp, etc. 
• Books and ebooks: Automate the boring stuff with Python, Python crash course, Think Python: How to think like a computer scientist. 
• Community and Forums: Reddit’s r/learnpython and Python Discord. 

However, this method usually takes more time, effort and dedication—and might not fit every learner.

Guided learning 

If you prefer structure and want to avoid jumping from one resource to another, guided learning is for you. This approach comes with support from instructors or mentors who provide expert guidance and speed up the learning process. It also helps you build practical skills faster and create a professional portfolio. 

Most guided learning platforms also offer certifications to validate your skills—a huge plus if you’re looking to land a programming gig. Platforms to consider: 

• Mimo’s Python Developer Career Path: This is the best option for beginners looking to build practical skills for the job market. It combines bite-sized lessons with interactive exercises and coding challenges to help you master the basics quickly. The platform allows you to work on projects and build your portfolio. You’ll also have access to a community of like-minded learners for motivation and support. 

• Coursera: Offers a vast selection of Python courses from top universities and companies. You’ll find options ranging from beginner-friendly introductions to specialized programs in data science, machine learning, and web development.

• edX: Partners with prestigious institutions like Harvard and MIT to offer university-level Python courses. If you’re looking for rigorous, academic-style learning, edX is an excellent choice.

3. Get an intro to Python

After choosing your learning path, it’s time to dive into the basics of Python. Start with exploring the most fundamental concepts:

• Creating variables: Learn how to store data like numbers, text, or other values in containers called variables for later use. For example, age = 25 (This stores the number 25 in a variable named age)

• Using variables: Explore how to access and manipulate the data you’ve stored in variables to perform calculations or make decisions in your code. For example, print(age + 5) (This adds 5 to the value stored in the age variable and prints the result)

• Formatting strings: Explore techniques to customize text output by inserting variable values or special characters into strings. For example, print(f”You are {age} years old.”) (This prints “You are 25 years old.”)

• Comparing numbers and strings: Understand how to use operators like “greater than,” “less than,” and “equal to” to compare values and make your code respond accordingly. For example, if age >= 18: print(“You are an adult.”) (This prints “You are an adult.” only if the age is 18 or more)

• Types and comparisons: Learn about the different types of data (e.g., numbers, text) in Python and how to make sure you’re comparing apples to apples, not apples to oranges. For example, 5 == “5.” (This comparison is False because a number is not the same as a string containing the same digits)

• Input: Figure out how to get information from the user while your program is running, making it interactive and dynamic. For example, name = input(“What’s your name? “) (This asks the user for their name and stores it in the name variable)

If you decide to take a Python course, the final list of essential topics will depend on the curriculum.

For example, Mimo’s “Intro to Python” covers various themes, including working with variables, formatting strings, discovering types, and more.

4. Build your first Python project

The best way to learn Python? Start building real-life projects right away. Getting too caught up in theoretical tasks often slows down the learning process. Instead, try applying new skills in practice.

For example, each section in Mimo’s Python Career Path includes interactive projects like building a bot conversation.

The guided tutorials come in small, actionable steps with increasing complexity to help you become proficient. 

5. Learn intermediary Python skills

After mastering the basics, it’s time to level up your Python game. Focus on the following intermediate concepts:

• Flow control: The backbone of decision-making and repetition in Python programs.

• Lists: Versatile collections of items (like numbers, words, or other objects) that can be ordered, changed, and accessed individually using their position or index.

• Functions: Reusable blocks of code that perform specific tasks. They help organize code and avoid repetition.
• Tuples are similar to lists but can’t be changed once you create them. They’re perfect for storing information you know won’t need to be modified, like a person’s name, age, and job title. 
• Dictionaries: They store information as key-value pairs. For example, you could have a dictionary where the keys are names and the values are phone numbers. You can look up a phone number by searching for the person’s name.
• Sets are collections of unique items that don’t allow duplicates. This is handy if you want to ensure that your data doesn’t contain repeated entries.
• Modules: Reusable pieces of code stored in separate files. They allow you to organize your code into manageable sections and reuse it across multiple projects. 
• APIs: Interfaces that allow your program to interact with other software. Using APIs can enable your programs to leverage external services and data.
• String and Lists operations: Mastering these will help you become proficient at sorting items, searching within text data, and manipulating elements to generate desired results 
• Object-oriented programming (OOP) is a way to organize computer programs by grouping data and actions together into reusable units called objects. For example, each character, item, and enemy in a video game is an object with its own properties and actions. When studying OOP, you master concepts like classes, inheritance, and polymorphism.

Mimo has all those topics covered within the same Career Path:

6. Design your portfolio in the process

A well-crafted coding portfolio shows your abilities and helps you stand out to potential employers or clients. Start by adding each test project you complete. Include a description, the tools and technologies used, and the results achieved. It’s important to provide context and highlight your problem-solving skills. There are many ways to create sample projects for your portfolio:

• Craft mini-projects: Create small, personal projects showcasing your coding skills. For example, you could create a website for a friend or a simple app.
• GitHub: Host your code on GitHub. It acts as your online resume, showing your problem-solving skills.
• Open source: You can also contribute to existing open-source projects and learn from experienced developers.
• Participate in online challenges: Test your skills and build small projects through online coding challenges. 

If you’re learning with Mimo, you can simplify this task by using its portfolio builder. At the end of the Python Career Path, you’ll have eight ready-to-go projects for your portfolio.

For example, Tomasz created a competitive portfolio and kicked off his career as a web developer.

7. Become a part of the coding community

There are many advantages to joining a coding community. You can quickly find answers to your questions, learn from others’ experiences, and gain insights into solving common problems. Communities and forums to check out:

• Official Python forum: This is the central hub for all things Python, where you can ask questions, participate in discussions, and stay up-to-date on the latest developments.
• r/learnpython (Reddit): A subreddit dedicated to Python learners, with plenty of resources, tutorials, and support from fellow learners and experienced developers.
• PySlackers (Slack): An active Slack community for Python enthusiasts, with channels for various topics and skill levels.
• Stack overflow: A popular Q&A platform where you can ask questions and share solutions.
• Local Python user groups: Many cities have local Python user groups that hold meetings, workshops, and other events. Check the Python website for groups near you.
• Mimo’s community: If you’re using Mimo, you can connect with the community to get guidance, share insights, and collaborate with your fellow learners.

The Top Python Careers for 2025

As we have already discovered, the Python job market offers many opportunities, and this trend will only continue to grow. Here are some roles you might come across:  

• Web developer: Building and maintaining websites or web applications using a complex Python web framework like Django or Flask. Here, you’ll need a solid grasp of Python basics, HTML, CSS, and JavaScript.
• Data analyst: Collecting, cleaning, analyzing, and visualizing data using Python libraries like Pandas, NumPy, and Matplotlib. Go for this if you have strong analytical skills and familiarity with statistics.
• Software engineer: Developing and testing software applications using Python. This position requires a deep understanding of software development principles, algorithms, and data structures.
• Backend engineer: Building the server-side logic of web applications, handling databases, APIs, and security. Backend engineering requires in-depth knowledge of Python frameworks, databases, and cloud technologies.
• Data scientist: Using Python to extract insights from complex datasets, build predictive models, and apply machine learning techniques. You’ll thrive better here if you have (or are willing to acquire) strong Python and data science skills, including working with libraries like scikit-learn and TensorFlow.
• Machine learning engineer: Designing, developing, and deploying machine learning models in production environments. To thrive, you need expertise in Python, machine learning algorithms, and cloud infrastructure.
• Python architect: Defining the technical architecture of Python-based systems, making critical decisions about technologies and frameworks. This role requires a deep understanding of the Python ecosystem and experience in system design.

To find Python jobs, explore online job boards like LinkedIn, Indeed, Glassdoor, and SimplyHired. For freelance opportunities, use platforms like Upwork, Freelancer, and Toptal.

The best ways to learn Python: resources 

Here are some of the resources you can use to learn Python faster.

Online courses and tutorials

• The Python Career Track by Mimo
• Harvard’s CS50 Introduction to Programming with Python
• Programming for Everybody (Getting Started with Python) on Coursera

Books and written resources

• “Automate the Boring Stuff with Python”
• “Python Crash Course” (3rd Edition)
• Real Python

Video tutorials and channels

• Corey Schafer’s YouTube Channel
• Programming with Mosh 

Learning tools and practice platforms

• Mimo’s code builder tool (included in the subscription)
• PartyRock.aws (AI playground)
• AWS Lambda (for hosting and testing Python code)
• AWS Skill Builder

FAQs

Let’s address some of the most common questions about learning Python.

Is Python easy to learn?

Python is considered one of the easiest programming languages to learn, especially for beginners. It has a simple, readable syntax and a large, supportive community. Many concepts in Python are straightforward, making it a great first language for those new to coding.

How much Python do I need to know to get a job?

To get an entry-level Python job, you should understand the basics, like data types, control structures, functions, and object-oriented programming. Familiarity with common libraries (like NumPy or Pandas) and version control (Git) is also valuable. Make sure to build a portfolio of projects to showcase your skills to potential employers.

Is Python a high-paying job?

Python skills can lead to well-paying jobs, especially in fields like data science, machine learning, and web development. Salaries vary based on experience, location, and specific role, but Python developers often earn competitive wages in the tech industry.

For example, Python developers make an average of $130,940/year or $62.43/hour in the US as of July 2024.

What is the salary for junior Python developers?

Entry-level Python developers can expect salaries of around $70,000 per year, depending on the company, location, and specific role. 

As you gain experience and skills, your earning potential increases. 

Keep in mind that salaries can vary significantly based on factors like the cost of living in different areas. 

At the same time, there are many remote Python developer jobs, meaning you could essentially work from anywhere.

Which is better, Java or Python?

Neither Java nor Python is universally “better” — each has strengths. Python is often easier to learn and read, making it great for beginners and rapid development. 

Java is widely used in enterprise environments and Android development. Choose based on your goals: Python for data science or scripting, Java for large-scale applications, or Android apps.

How to learn Python faster?

To learn Python faster:

• Practice coding daily, even if just for short periods.
• Work on projects that interest you and keep you motivated. 
• Use interactive coding platforms and join online communities to get feedback. 
• Break down complex concepts into smaller, manageable parts.
• Use interactive platforms like Mimo that help you learn by doing.

Conclusion

Python is a dynamic and popular coding language that’s easy to pick up, making it a perfect choice for beginners. You can use it to build a career in various fields, from data science to engineering. To get started: 

1. List your learning goals.
2. Figure out what motivates and excites you the most.
3. Dive into the basics like variables, lists, and functions. 
4. Practice by creating small projects and keep exploring more complex topics.
5. Join the Python community for help and inspiration. 
6. Create your portfolio and start applying for jobs.

With dedication and the right resources, you can become a Python pro quickly. The job market for Python developers is hot right now, and learning it can open many doors.

Ready to get started? Mimo can help you master Python and build a portfolio with practice-led and interactive lessons. Start for free today!