Data Literacy Articles

In the third entry of data demystified, we’ll define the most common pieces of jargon you hear in data science today. From machine learning to deep learning, here’s all the subfields of data you need to know.

In the fourth entry of data demystified, we’ll break down the four types of analytics. From a descriptive to prescriptive, we’ll look at how analytics can answer the most pressing questions.

In the fifth entry of data demystified, we provide an overview of the basics of descriptive statistics, one of the fundamental areas of data science.

In the final part of data demystified, we outline the most common types of AI bias, and why data literacy helps avoid harmful impacts from AI.

In part six of data demystified, we’ll break down one of the biggest fallacies in data: Correlation does not imply causation

We’re excited to announce our four-part webinar series covering organizational data maturity. Sign up and gain a full overview of what is required to become a data-driven organization.

Discover the most in-demand data skills and why employers are seeking skilled individuals. Plus. find out how you can improve your data knowledge in key areas.

Improve your students’ data literacy by working on collaborative data science projects.

Discover why data literacy matters and learn how it can help your team thrive in an increasingly data-driven world.

DataCamp grew by over 400% in the past three years, making it the second fastest growing education company, and the 167th fastest growing company in North and South America.

Learn about use cases in data science and discover how data science can be implemented in various industries to drive growth and decision-making.

Interested in learning Power BI but don't know where to start? Read this guide for step-by-step learning and resources to keep practicing what you learned