Computer Science Basics
Fundamental principles and concepts
HarvardX: Data Science: Visualization
Learn basic data visualization principles and how to apply them using ggplot2.
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Course Insight
Suitable for beginner learners. This course serves as an entry point into Computer Science, building foundational knowledge before moving on to advanced frameworks or specialized paths.
Beginner FriendlyCertification IncludedSelf-Paced Learning
SKILLS TO
MASTER
Practical ApplicationTrending
Real-world project implementationBest Practices
Industry standard workflows and guidelinesCareers:Data Scientist, Data Analyst, Machine Learning Engineer.
Quick Facts
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What You’ll Learn
As part of our Professional Certificate Program in Data Science, this course covers the basics of data visualization and exploratory data analysis. We will use three motivating examples and ggplot2, a data visualization package for the statistical programming language R. We will start with simple datasets and then graduate to case studies about world health, economics, and infectious disease trends in the United States.
We'll also be looking at how mistakes, biases, systematic errors, and other unexpected problems often lead to data that should be handled with care. The fact that it can be difficult or impossible to notice a mistake within a dataset makes data visualization particularly important.
The growing availability of informative datasets and software tools has led to increased reliance on data visualizations across many areas. Data visualization provides a powerful way to communicate data-driven findings, motivate analyses, and detect flaws. This course will give you the skills you need to leverage data to reveal valuable insights and advance your career.
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Outcomes
- Data visualization principles.
- How to communicate data-drivenfindings.
- How to use ggplot2 to create custom plots.
- The weaknesses of several widely-used plots and why you should avoid them.
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