How to Learn Python (Step-by-Step)

1. You Can Automate Tasks

Python is a versatile programming language, which means there's something in it for everyone. Once you learn some Python basics, you'll be able to do things like:

• Work with massive datasets easily
• Scrape data from the web and access APIs
• Use it to power-up your work in Excel
• Automate all sorts of tasks

Learning to automate tasks independently can be incredibly powerful because your time is valuable. Let the robots send your emails and fetch data from the internet. And if you're feeling extra ambitious, you can even create the next coffee delivery app to get your caffeine fix every morning easily. (That may take a little bit more work, though.) More likely, you'll be able to start finding creative solutions for the people and companies you work for. As you learn how to program in Python, you’re literally learning a new language that is designed for identifying and predicting patterns. As you find patterns, you'll be able to communicate those findings in a way that makes a big impact in your industry and the world.

2. You Can Impress Your Boss

Knowing Python is a powerful way to stand out at work (or land that promotion you’ve been eyeing). To non-programmers, coding often feels like a superpower—it lets you amplify your skills and get far more done in less time. Python makes it easy to gather data, uncover insights, and turn numbers into actionable solutions. Imagine automating tasks like web scraping, sending emails, or analyzing supply chains to find cost-saving opportunities or improve quality control. If your boss has mentioned data science as a growth area, learning Python online through a self-paced course could be the perfect way to build your skills and advance your career without disrupting your routine.

3. It Creates Exciting New Career Opportunities

If you’re ready for a career change or feeling stuck in your current role, picking up some Python skills could be your next step. The demand for Python developers—especially in data science—has never been higher. Data science offers rewarding work, excellent pay, and often the flexibility to work remotely for top companies. As a newer field, data science values results and practical skills over traditional requirements like a four-year degree. Many of our alumni have landed fulfilling roles, both in offices and remotely, after completing our Data Science paths. Our courses are designed to give you a competitive edge with hands-on experience working with real-world data and a portfolio of projects that showcase your skills—often more impactful to employers than a degree.

4. Build the foundation to learn AI and Machine learning

When it comes to generative AI, Python's significance cannot be overstated. It serves as the foundation for AI and machine learning, with key frameworks like TensorFlow and PyTorch relying on Python for development and innovation. Its effectiveness in automating tasks and analyzing large datasets is central for training AI models. Python's seamless integration with AI tools and its widespread use in AI research makes it indispensable for anyone interested in this field.

It can certainly be challenging at times. However, if you take the step-by-step approach I’ve outlined here, you’ll find that it’s much easier than you think. Python is actually considered one of the easiest programming languages to learn. And while anyone can learn it — even if you've never written a line of Python code before — you should expect that it will take time, and you should expect moments of frustration.

Sure, it's possible. There are many free Python learning resources available to you. At Dataquest, for example, we have dozens of free Python tutorials that can support your learning.

The downside to free resources is the lack of structure; you’ll need to patch together several free resources to get a well-rounded education. This means you’ll spend extra time researching what you need to learn next and how to learn it. You may find that you've wasted time learning the wrong things or often get stuck because you lack the prerequisite knowledge to complete a project or tutorial.

Premium platforms may offer better teaching methods (like the interactive, in-browser coding Dataquest offers) and save you time finding and building your own curriculum.

Yes. Python is a great language for programming beginners because you don’t need prior experience with code to pick it up. Dataquest helps students with no coding experience get jobs as data analysts, data scientists, and data engineers.

If you’re looking for a general answer, here it is: Learning the Python basics may only take a few weeks. However, if you’re pursuing a career as a programmer or data scientist, you can expect it to take four to twelve months to learn enough advanced Python to be job-ready. (This estimate comes from learners who have taken our Python for Data Science career path.)

The personalized answer depends on several factors. The good news: it is probably less than you think if you take the right approach. Let’s look at some examples …

• A Marketer Who Wants an Edge: If you're a marketer who'd like to analyze Google Analytics data more rigorously, you could learn fundamental Python syntax and the required pandas techniques in a matter of weeks. This wouldn't make you a job-qualified Python developer or data analyst, but it would be enough to solve your problem.

• A Begineer Seeking a New Career in Data Science: If you're just getting started with Python and are looking for full-time work using Python, you can expect to spend at least a few months studying part-time. How many months will depend on the job you're looking for. Working through our Data Analyst in Python career path, for example, would prepare you to apply for jobs as a Data Analyst. Most learners take at least three months to complete this path. To be clear, though, you could spend a lifetime learning Python. There are hundreds of libraries, many of them regularly improving and evolving, and the language itself also changes over time. It doesn't take too long to become capable of solving problems with Python, but to master Python means continually learning and growing over the course of your career.

• Exploring a career in web development or software engineering: If you're keen on web development and want to use Python to do it, our Generative AI Fundamentals in Python skill path is a great place to start. In weeks, you'll grasp Python fundamentals tailored for web development, work with numerical and text data, make API calls to the web, and build your own projects.

Yes. It is still worth it from a career outlook, financial return, and versatility perspective.

1. Demand for Python skills is High

   Python's importance in the tech industry is indisputable, particularly in fields like machine learning and artificial intelligence, where it’s the language of choice for many. Its rise as the most used language on GitHub, overtaking JavaScript, highlights its growing role in data science and machine learning projects. With the global machine learning market projected to reach $79.29 billion this year, professionals proficient in Python are highly sought after. Python skills not only open doors to diverse and lucrative career opportunities but also enhance your overall employability. With its applications spanning multiple roles—from data analysis to software development—learning Python is an invaluable investment for anyone navigating today’s job market.

2. Lucrative Salaries

   Careers that require Python skills can earn salaries well over $100,000 per year in the United States. Here’s a list of jobs requiring Python programming knowledge — and their U.S. salaries:

   • Entry Level Data Analyst: $55K–$83K (become one here)
   • Data Analyst: $66K–$103K (become one here)
   • Data Engineer: $103K–$152K (become one here)
   • Data Scientist: $130K–$190K (become one here)
   • Software Engineer: $113K–$174K
   • Python Developer: $89K–$128K
   • Deep Learning Engineer: $118K–$181K
   • Machine Learning Engineer: $124K–$186K



3. Incredible Versatility

   There's an inside joke in the Python community that Python is the second-best language for everything. Of course, what’s best is subjective, but there's no denying that Python is incredibly flexible. It’s the most commonly used language for data science and machine learning. One reason for its widespread popularity is that it’s one of the easier languages to learn and use when working with data. And, fortunately for employers and data scientists alike, it doesn't require years of study to master.

Yes, it's very possible to teach yourself Python on your own. There are many learning resources available on the web to help you with everything from web development to artificial intelligence. Here at Dataquest, we've helped thousands of students learn Python and get jobs in data science, all on their own schedules and from the comfort of their own homes. Teaching yourself Python does take time, though. You must also be sure that you're writing code and applying what you learn in real-world scenarios rather than just watching lecture videos and answering multiple-choice questions. Taking the right approach can also be the difference between success or failure when you're learning through self-study.

If you're learning on your own, creative time-management habits will be very helpful — especially if you want to pick up Python sooner rather than later. While five hours may seem like a lot to fit into your already-busy weekly schedule, it's very achievable for someone working a full-time job — or with a full calendar of school commitments. Here are a few ways you might find the spare hours …

• Set your alarm alock for 30 minutes earlier: The best time you can set aside for learning each day is in the morning. Biologically, your best, most productive time is around the first two hours of each day. You don't want to sacrifice any sleep, but you may want to get to bed earlier so you can practice a bit before work. It's a commitment, for sure. But, if you set aside your clothes the night before, have your coffee ready to go, and already know what aspects of Python you are going to work on, it's a bit easier. Tell yourself that you can't look at your phone or emails until you dedicate 30 minutes to learning Python, and make it a habit! The time it saves and the advancement in your career will be worth the extra effort. As an added benefit, you'll feel extra healthy when you get a productive head start on your day.

• Log off your evening Netflix habit: If you already wake up at 5 am to get to work each day, waking up earlier may not be the best option for you. In that case, you might take the first two hours when you get home from work each day to dedicate to learning. If you’re overwhelmed by the idea of finding two hours between your commute, gym, dinnertime, and downtime, spend a week really looking at how you spend your evenings. Write down exactly what you did each day this week:
  • How much time did you spend on Netflix?
  • Did you waste a few hours on social media?
  • Did you get lost scrolling through Amazon?
  • Can you do meal prep on Sundays to save time spent on weeknight cooking?

• Take advantage of quiet Saturday mornings: We've seen that practicing every day is the best way to master Python as quickly as possible. It's important to be consistent, but sometimes life gets in the way. That's what weekends are for. If you're completely booked from 5 am to 6 pm every day, you can keep yourself on track by putting in extra hours on the weekend. Plus, this is a great way to find uninterrupted time in a space you've dedicated just for learning Python. One thing to keep in mind: studying two hours a day is far better than ten hours in one day on the weekend. If you have other commitments during the week, even ten minutes each morning will make a difference compared to only looking at Python materials once a week.

• Join A Community of Python Programmers: Joining a community of Python developers will help you stay on track toward your goal to learn Python. Python meetups are fairly common on Meetup.com, and you'll get recommendations from other members of these groups. Additionally, Dataquest's students use our Members' community to network and discuss Python problems, troubleshooting, and data science portfolio projects. If you carve out a few minutes each day for networking, you'll complete your coursework with a new skill and a new network as you enter the job market!

• Find a Project you are interested in working on: The best way to learn how to complete data projects is by building data projects. Dataquest learners spend their time working through real-world data challenges that teach learners to combine multiple skills and tools to solve a problem or accomplish a task. Projects created out of genuine curiosity stand out, as opposed to those made just for the sake of it. Take your time to find a topic that captures your attention or choose from hundreds of data science projects on the Dataquest learning platform.

• Compete on Kaggle: Kaggle hosts data science competitions. Signing up is free, and members submit Python scripts to find the best model for a given dataset. You'll find a lot of competitions with objectives similar to the guided projects in your Dataquest portfolio. If you're one of those Fortnite fans we mentioned above, collaborating with other Dataquest students on Kaggle competitions can help replace some of your game time in a way that helps you learn Python without losing that competitive fix!

Probably not. In data science, certificates don’t carry much weight. Employers care about skills, not paper credentials.

Translation? A GitHub full of great Python code is much more important than a certificate.

Many jobs can benefit from Python skills. Here are a few careers that you can break into if you know Python:

• Python Developer
• Data Analyst
• Data Scientist
• Data Engineer
• Business Analyst
• Machine Learning Engineer
• Software Engineer

Yes. Python is a popular and flexible language that’s used professionally in a wide variety of contexts.

We teach Python for data science and machine learning in Python, but you can also apply your skills in other areas. Python is used in finance, web development, software engineering, game development, and more.

Having some data analysis skills with Python can also be useful for various other jobs. If you work with spreadsheets, for instance, there are likely things you could be doing faster and better with Python. 

Plenty of online Python courses, books, boot camps, and free guides online exist. We always recommend Dataquest, but we're a bit biased.

Basic Python skills you'll need to learn include:

• Python lists
• Python loops
• Python strings
• Python functions
• Python arrays
• Python operators
• Python syntax
• Etc

Here at Dataquest, we get you up to speed on the basics quickly so you can jump into fun projects as soon as possible. Try our introductory Python course and see for yourself. Happy coding!