Learn Python for Data Science from Scratch
It’s virtually impossible to succeed at anything without a solid understanding of the fundamentals. That’s why we take particular care in ensuring that our introductory courses, the gateways to data science, are as well-crafted as possible.
Today, we’re announcing the re-launch of our introductory Python course, Python for Data Science: Fundamentals. It’s available right now, and the entire course is free.
Our basic Python course has helped tens of thousands of students to date, but when we took a look at the old course, we knew we could do an even better job. The revamped course, which is written by data scientist Alex Olteanu, focuses on covering the fundamentals with clearer explanations, better visuals, and more hands-on learning with real-world data.
It’s also designed to make it easier for anyone to dive into and start learning, even if they have no previous programming experience.
What’s special about this course
In the revamped course, you’ll find a clear, approachable introduction to programming in Python that anybody can learn from. But it’s specially tuned to help aspiring data scientists move quickly from zero programming skills to mastery of the basics needed to work with data in Python.
By the end of the course, you’ll be working with real-world data sets that have thousands of rows. You’ll be comfortable with Jupyter Notebook (one of the most popular tools in the world of data science). And you’ll have completed challenging exercises that prove you’ve really mastered the material.
The new course has been carefully designed to link together fundamental Python programming skills and concepts, so that each new thing you learn builds off the previous one. You’ll learn about the very basics (like simple arithmetic, variables, and data types), lists and for loops, conditional statements, dictionaries and frequency tables, and functions. Then you’ll work through a guided project that puts all of that knowledge together to solve a real-world data science problem analyzing mobile apps.
By the end of the course, you’ll have a great foundation and the first data science project for your portfolio.
What’s special about Dataquest
Obviously, there are lots of places where you can learn basic Python coding skills, and we encourage students to seek out whatever resources work best for them. But if you’re interested in learning Python for data science, we have some unique advantages you may not find elsewhere:
- Unique platform with a hands-on learning focus. We want to get you working with code and experimenting with each new concept as quickly as possible. You’ll never go more than a minute or two without having the chance to apply something you’re learning, and with our platform, you can write and check Python code right in the browser window.
- Easily searchable, text-based content. Videos can be fun, but if you have to watch a 30 minute video before you get the chance to apply anything you’ve learned, you’re going to waste lots of time scanning back through the video trying to find the right moments to review concepts you’ve already forgotten. Dataquest’s text-based learning content more accurately reflects the reality of working as a data scientist (where you’ll often need to consult written documentation) and it’s incredibly easy to search through previous lessons and find what you want.
- Real-world data and interesting projects. It’s difficult to feel inspired to learn if you’re working with boring, fake data on projects that don’t mean anything. That’s why we use real-world data to answer real-world questions, and help you build projects you can use in your data science portfolio when you’re applying for jobs.
If you’re looking to learn Python for data science, we’re confident this is the best jumping-off point you’ll find. And since the entire course is completely free, you’ve got nothing to lose: start learning Python for Data Science today.
Commit to your data science study with a Premium subscription, now 50% off for a limited time when you sign up for an annual plan.
Charlie is a student of data science, and also a content marketer at Dataquest.