Learn how to navigate the business environment as a data pro, including how to communicate your analysis results to a non-technical audience. Once you've got the skills to do great data work, here are five tips that'll help you make sure people actually listen to what you have to say!
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Is Dataquest worth it in 2020? We asked over 600 Dataquest learners at all stages of their learning journey for reviews and then analyzed the data.
Learn R programming for data analysis from right in your browser while writing real code and working with real data. Now, free for a limited time! Exciting news: for the next week, all of our R programming courses are free. In fact, every single course in our Data Analyst in R career path is free from July 20-27.
Python programming is a critical skill for data engineers. When it comes to working with data, there's a powerful library that can increase your code's efficiency dramatically, especially when you're working with large datasets: NumPy.
Learn the skills you need to become a data engineer with our new interactive data engineering course path, which covers Python, SQL, Postgres, and more!
Learn how to navigate the business environment as a data professional, including how to communicate your analysis results to a non-technical audience.
Being a data engineer means helping others work with data efficiently, which means assessing, optimizing, and implementing algorithms for your use case.
In this course, you'll learn about the basics of conditional probability and then dig into more advanced concepts like Bayes's Theorem and Naive Bayes algorithms.
Should you enroll in an online data science bootcamp or try one of the expensive offline schools? Compare your options stack for learning data science.
There are lots of ways to learn data science, but the best approach is with an active curriculum that focuses on hands-on learning.
Learning to write better code — code that's readable, maintainable, and debuggable — is a crucial skill for being an effective part of a data science team.