Python Tutorials for Data Science

python tutorials for data science

Looking to beef up your Python programming skills? In addition to our interactive online programming and data science courses, our blog also features many free Python tutorials on topics including everything from for loops to machine learning.

Whether you want to brush up on your web scraping skills, review linear regression, beef up your data viz designs, or get better at cleaning your data, you'll find tutorials here that can help!

First things first, though: these articles can help you get your Python learning journey off on the right foot:

Interactive Python Courses - Start Free!

If you're just getting started on your Python journey, the best thing you can do is give yourself a great foundation in the fundamentals. Our introductory Python courses are interactive, and will allow you to apply what you're learning as you learn it.

You don't need any prior programming experience, and by the time you finish, you'll have built a real-world data science project from the ground up using your new Python skills!

Beginning Python Tutorials

If you're at an early stage in your Python journey, these tutorials will help you solidify your command of basic concepts like lists, dictionaries, for loops, functions, and more. If you've never written a line of code before, we'd recommend you start with our Python Fundamentals course, which will help you learn Python from scratch. But if you've already spent a little time learning Python, these tutorials will help you go deeper and reinforce the skills you've already learned.

Python Tools

If you're going to do Python programming, particularly for data science, it helps to know the best tools to use. These Jupyter Notebooks tutorials will take you from a notebooks newbie to an expert who knows all the tips, tricks, and shortcuts. 

Working With Data

If you want to do data analysis in Python, you'll need to be able to access, collect, and manipulate data. These Python tutorials will walk you through various aspects of data collection and manipulation in Python, including web scraping, working with various APIs, concatenating data sets, and more. Or go hands-on with our SQL, web scraping, and API courses for data science.

Data Cleaning Tutorials

Machine learning may be the part of data science that gets all the headlines, but the reality is that most data scientists say they spend more time cleaning data than doing any other single task. These Python data cleaning tutorials will help you beef up your data cleaning and data munging skills by walking you through the process of scrubbing data for a variety of projects. Want to take things to the next level? Check out our introductory and advanced data cleaning courses.

Python Data Analysis Tutorials

Once you've got your data set up in Python, it's time to do some number-crunching! These Python tutorials will help you reinforce your data analysis skills by walking you through a variety of different data science projects and different types of analysis. They'll also help you dig into the statistics concepts that underlie these analyses. Or, build an even deeper understanding with our hands-on data analysis and statistics courses.

Data Visualization Tutorials

Data analysis is only as as valuable as it is understandable. These tutorials will help you improve your data visualization skills and master crucial Python data viz libraries like Matplotlib and Seaborn. Or, take your learning to the next level with one of our interactive data visualization courses.

Python Machine Learning Tutorials

Machine learning is a huge and complex area of data science, and it's a skill that every data scientist needs to have in their tool set. Reinforce your machine learning skills with these tutorials, which will walk you through working with a variety of different algorithms using real-world data sets. Or, take your learning to the next level with our interactive machine learning courses.

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Python Learning Resources

Tutorials and online courses can't cover everything, and whether you're still in the early stages of learning or already an advanced Python programmer, you're going to have to refer to the documentation every now and then. Here are some helpful links for finding quick answers to your questions.