Free
CoursePrinciples of Data Literacy
Discover the world of data in this fully conceptual course where you will learn how to think about, visualize, and analyze data.
This course includes
This course includes
Skill level
BeginnerTime to complete
Average based on combined completion rates — individual pacing in lessons, projects, and quizzes may vary4 hoursProjects
3Prerequisites
None
About this course
This no-code course introduces the foundational how’s and why’s of data. How do statistics help us make conclusions from data? Why is good design critical for communicating data stories through data viz? What are the different kinds of analysis we can perform on a dataset? This course will help you feel empowered to answer these questions (and more!) and work with data with confidence.
Skills you'll gain
Evaluate data quality
Interpret statistical conclusions
Create and read data visualizations
Analyze data responsibly
Understand the role generative AI can play in you data analyses
Syllabus
9 lessons • 3 projects • 6 quizzesCertificate of completion available with Plus or Pro
Earn a certificate of completion and showcase your accomplishment on your resume or LinkedIn.
Projects in this course
- practice Project
Statistical Thinking Lab: Movie Statistics
In this lab, you'll step into the role of a film industry analyst examining streaming service content trends. Using real Netflix film data, you'll practice interpreting and applying summary statistics to uncover insights about film production patterns. - practice Project
Simplifying Statistics with Prompt Engineering: Coffee Shop Sales Project
Explore coffee shop sales data across multiple locations to uncover insights and trends using statistical analysis. This project focuses on crafting effective prompts to analyze complex data and generate actionable insights, enabling informed business decisions without the need for manual calculations, coding, or visualization tools. In this project, you’ll work with coffee shop transactional sales to: + Understand data distributions to identify patterns and trends. + Calculate and compare central measures (mean, median) for key insights. + Measure variability and detect outliers in the data. + Investigate relationships between categorical and numeric variables. + Apply statistical principles to uncover meaningful business insights. - practice Project
Data Visualization Basics Lab: Backyard Birder's Association
In this lab, make choices to recognize effective data visualization design.
Meet the creator of the course
Eva Sibinga
Curriculum Developer at CodecademyEarn a certificate of completion
Show your network you've done the work by earning a certificate of completion for each course or path you finish.- Show proofReceive a certificate that demonstrates you've completed a course or path.
- Build a collectionThe more courses and paths you complete, the more certificates you collect.
- Share with your networkEasily add certificates of completion to your LinkedIn profile to share your accomplishments.
Principles of Data Literacy course ratings and reviews
294 ratings
- 5 stars
- 4 stars
- 3 stars
- 2 stars
- 1 star
- The progress I have made since starting to use codecademy is immense! I can study for short periods or long periods at my own convenience - mostly late in the evenings.ChrisCodecademy Learner @ USA
- I felt like I learned months in a week. I love how Codecademy uses learning by practice and gives great challenges to help the learner to understand a new concept and subject.RodrigoCodecademy Learner @ UK
- Brilliant learning experience. Very interactive. Literally a game changer if you're learning on your own.John-AndrewCodecademy Learner @ USA
Our learners work at
Join over 50 million learners and start Principles of Data Literacy today!
Looking for something else?
Related resources
- Article
R Programming Language Explained (Careers, Use Cases, Difficulty)
Explore what the R programming language is, its features, pros and cons, use cases, careers, and how it compares to Python. Learn how R is used in data science and how easy it is to learn. - Article
Intro to Data Acquisition
Exploring and defining the methods of obtaining data - Article
Why Data Structures?
Learn what data structures are, why they are useful, and how you can use them effectively.
Related courses and paths
- BI Data Analysts use Python and SQL to query, analyze, and visualize data — and Tableau and Excel to communicate findings.
- Includes 18 Courses
- With Certificate
- Beginner Friendly.50 hours
- Data Analysts and Analytics Data Scientists use Python and SQL to query, analyze, and visualize data — and communicate findings.
- Includes 22 Courses
- With Professional Certification
- Beginner Friendly.70 hours
- This course is for new programmers who aren't sure what they want to learn about. Take this course to jumpstart your learning journey!
- Beginner Friendly.1 hour
Browse more topics
- Data analytics3,136,310 learners enrolled
- Data science5,236,246 learners enrolled
- Code foundations8,417,512 learners enrolled
- Computer science6,906,900 learners enrolled
- Web development5,645,248 learners enrolled
- Python4,232,547 learners enrolled
- For business4,032,953 learners enrolled
- JavaScript3,170,859 learners enrolled
- IT3,084,895 learners enrolled
Unlock additional features with a paid plan
Practice Projects
Guided projects that help you solidify the skills and concepts you're learning.Assessments
Auto-graded quizzes and immediate feedback help you reinforce your skills as you learn.Certificate of Completion
Earn a document to prove you've completed a course or path that you can share with your network.