In the era of big data, acquiring the ability to analyze and visually represent “Big Data” in a compelling manner is crucial. Therefore, it is essential for data scientists to develop the skills in producing and critically interpreting digital maps, charts, and graphs. Data visualization is an increasingly important topic in our globalized and digital society. It involves graphically representing data or information, enabling decision-makers across various industries to comprehend complex concepts and processes that may otherwise be challenging to grasp. DSCI 605 Data visualization serves as the foundation for understanding principles, concepts, techniques, and tools used to visualize information in large, intricate data sets. It also provides hands-on experience in visualizing big data using the open-source software R. Through the course, students will learn to evaluate the effectiveness of visualization designs and think critically about decisions, such as color choice and visual encoding. Additionally, students will create their own data visualizations and become proficient in using R.
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Data Visualization
Enseigné en Anglais
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Il y a 5 modules dans ce cours
In the first module, we will learn what is data visualization, why data visualization is necessary in data science field, what data visualization will do and what skills data visualization need. We will first get started with R by learning R basic and R Markdown to prepare the data visualization in the course.
Inclus
20 vidéos8 lectures4 quizzes1 sujet de discussion2 laboratoires non notés
Understanding the elements and components of data visualization is essential for data visualization because it provides a systematic framework for creating effective and meaningful visual representations of data.In this module, we will explore the grammar of graphics, explain some rational, and introduce principles in data visualization, as well as describe the common Exploratory Data Analysis (EDA) idioms' features and applications.
Inclus
8 vidéos2 lectures3 quizzes1 sujet de discussion
Let's get our hands wet with real data visualization-producing a graph. In this module, we will explore the powerful data visualization package ggplot2. In this module, you will learn basic usages of ggplot() function, the fill and color aesthetics, and learn to create a histogram using ggplot() and setting suitable bin numbers or bin width.
Inclus
8 vidéos5 lectures1 quiz1 devoir de programmation1 évaluation par les pairs1 laboratoire non noté
Now you have conducted the basic data wrangling, documented your work in R Markdown, and created your first data visualization in previous modules. In this module, you will learn to embed, create and refer to images and tables in R Markdown. In addition, you will learn to produce scatter plots, which further enrich your visualization experience and enhance your visualization skills.
Inclus
10 vidéos2 lectures1 sujet de discussion1 laboratoire non noté
This module will continue for one of the common EDA idioms-box plots to enrich your data visualization experience and will explore new technique-layout multiple plots on one page. In this module, you will learn to produce boxplots using ggplot(), interpret boxplots and arrange multiple plots on one page.
Inclus
7 vidéos3 lectures1 quiz1 devoir de programmation1 sujet de discussion1 laboratoire non noté
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University of Colorado Boulder
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Ce cours fait partie des programmes diplômants suivants proposés par Ball State University. Si vous êtes accepté(e) et si vous vous inscrivez, votre travail en cours pourra être pris en compte pour l’obtention de votre diplôme et vos progrès pourront être transférés.
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