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Introducing the Applied Data Science Lab
Introducing the Applied Data Science Lab

How is the Applied Data Science Lab different from the Data Science Module?

Nicholas Cifuentes-Goodbody avatar
Written by Nicholas Cifuentes-Goodbody
Updated over a week ago

If you have completed either Unit of our previous Data Science offering, you may be wondering whether pursuing the Lab is worth your time. Whether you are looking for new challenges or you’d like to brush up on your existing skills, we’d love to have you join!

Here’s a breakdown of the similarities and differences between the two offerings:

How is our new offering similar to the previous version?

  • No installation required: When you're accepted into the Applied Data Science Lab, you'll be given a virtual machine that comes with all the software you need to complete your work. So you don't need to worry about installing things on your computer; you can start doing data science from day one.

  • Real-time feedback: Whenever you submit a graded task, you'll receive instant feedback on your work. That way, you'll quickly know when you're on the right track or when you need to make corrections.

  • Live support: Each project in the Lab has a dedicated teacher who leads live office hours on Zoom. If you can't make the live sessions, you can always get support in the forum, and you'll always have access to office hour recordings.

  • Credentialed: When you complete the Lab you earn a sharable Credly certification.

What is different about the Lab?

  • All new content: All the projects in this program are new. That means new datasets, new topics, updated Python libraries, and even SQL and no-SQL databases to work with.

  • Self-paced: Juggling life and learning isn't easy, so we've made the program flexible to fit our students' schedules. Now you can start the course whenever you want, move at your own pace, and set your own deadlines. It doesn't matter whether you have 10 minutes a day to spare or 10 hours: The program is designed so that you can always make progress in your learning.

  • Flexible: Data Science draws on many subjects, but you don't need to master them all before starting the Lab. Whether you're new to programming in Python or feeling a little rusty on statistics, whether you've taken the previous version or are joining us for the first time, our curriculum is designed to give you extra support where you need it.

  • Project-based: We believe that the best way to learn new skills is applying them in a real-world project. The new data science curriculum consists of eight end-to-end projects, where you'll go from data acquisition and preparation, to model building and tuning, to sharing your work with technical and non-technical stakeholders.

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