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.

您将获得的技能
要了解的详细信息
了解顶级公司的员工如何掌握热门技能

该课程共有5个模块
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.
涵盖的内容
20个视频8篇阅读材料4个作业1个讨论话题2个非评分实验室
20个视频•总计87分钟
- Welcome to Data Visualization•5分钟
- Meet Your Instructor•2分钟
- Module 1 Overview•2分钟
- Introduction to Data Visualization•6分钟
- Data Visualization techniques•7分钟
- Some examples of data visualization•5分钟
- Introduction to R•4分钟
- RStudio Panes•2分钟
- Data types in R•3分钟
- Data structures in R•8分钟
- Introduction to objects in R•2分钟
- Create objects/variables in R•4分钟
- Create objects with different data structures in R•8分钟
- Remove and save objects•5分钟
- A Simple Tutorial to Get You Started with R•6分钟
- Introduction to R Markdown file•2分钟
- The Structure of an R Markdown File•3分钟
- Create Your .Rmd File and Use Knitr to Convert .Rmd to .html or PDF•2分钟
- Format the text in R Markdown•7分钟
- Code Chunks-Hide code and information•5分钟
8篇阅读材料•总计89分钟
- Meet Your Course Staff•5分钟
- Read the Course Syllabus•10分钟
- Install R and RStudio•30分钟
- RStudio Lab (In-Browser Option)•10分钟
- Materials for Understanding Basic R•1分钟
- RMarkdown Cheat Sheet•30分钟
- Install the "knitr" and "rmarkdown" Packages•2分钟
- Module 1 Summary•1分钟
4个作业•总计12分钟
- Activities and Skills in Data Visualization•3分钟
- Basic R information•3分钟
- Create Objects in R•3分钟
- R Markdown Basic Information.•3分钟
1个讨论话题•总计15分钟
- Introduce Yourself•15分钟
2个非评分实验室•总计120分钟
- Practice Lab: Getting Started with RStudio/R•60分钟
- Create your first R Markdown file by default and name it "My first R Markdown file"•60分钟
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.
涵盖的内容
8个视频2篇阅读材料3个作业1个讨论话题
8个视频•总计34分钟
- Module 2 Overview•2分钟
- Introduction to data visualization•4分钟
- Introduction to the Grammar of Graphics•3分钟
- Marks and Channels•2分钟
- Color models•5分钟
- Exploratory Data Analysis (EDA)•8分钟
- Some examples•3分钟
- Data Visualization Principles•7分钟
2篇阅读材料•总计26分钟
- Principles of Effective Data Visualization•25分钟
- Module 2 Summary•1分钟
3个作业•总计11分钟
- Components of Data Visualization•3分钟
- Color Systems•3分钟
- Best Practices in Data Visualization •5分钟
1个讨论话题•总计30分钟
- Why is Rainbow Color Not Suggested in Data Visualization?•30分钟
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.
涵盖的内容
8个视频5篇阅读材料1个作业1个编程作业1次同伴评审1个非评分实验室
8个视频•总计32分钟
- Module 3 Overview•2分钟
- Introduction to ggplot2•3分钟
- Basic usage of ggplot() function•8分钟
- Colors in ggplot()•7分钟
- Introduction to Histogram•1分钟
- Bins in Histogram•2分钟
- Plot a Single Histogram•1分钟
- Grouped Histogram•8分钟
5篇阅读材料•总计7分钟
- Installation of ggplot2•1分钟
- ggplot2 Cheatsheet•1分钟
- Change Histogram Outline and Fill Colors•2分钟
- Legends in ggplot2•2分钟
- Module 3 Summary•1分钟
1个作业•总计3分钟
- ggplot() Usage•3分钟
1个编程作业•总计60分钟
- Step 1: Grouped Histogram in R•60分钟
1次同伴评审•总计60分钟
- Step 2: Grouped histogram in R•60分钟
1个非评分实验室•总计60分钟
- Single histogram•60分钟
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.
涵盖的内容
10个视频2篇阅读材料1个讨论话题1个非评分实验室
10个视频•总计32分钟
- Module 4 Overview•2分钟
- Save graphs as png and jpeg•4分钟
- Output graphs into a pdf file•2分钟
- Embed images in R Markdown files•6分钟
- Refer to images in R Markdown files•2分钟
- Create tables in R Markdown•2分钟
- Index tables in R Markdown files•2分钟
- About scatter plots and bubble plots•3分钟
- A scatter plot with ggplot2•6分钟
- A scatter plot with ggplot2•4分钟
2篇阅读材料•总计31分钟
- Embed Images and Tables in R Markdown•30分钟
- Module 4 Summary•1分钟
1个讨论话题•总计40分钟
- Does a Scatter Plot Prove the Causation?•40分钟
1个非评分实验室•总计60分钟
- Ungraded Lab: A HTML report in R Markdown file with images and tables, and refer and index the tables•60分钟
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.
涵盖的内容
7个视频3篇阅读材料1个作业1个编程作业1个讨论话题1个非评分实验室
7个视频•总计34分钟
- Module 5 Overview•2分钟
- Introduction to Boxplots•3分钟
- Basic Box plot in R•6分钟
- Boxplot in R_Change outline colors and fill colors•4分钟
- Arranging multiple plots on a page•5分钟
- Use facets in ggplot2•6分钟
- grid.arrange() function•7分钟
3篇阅读材料•总计16分钟
- Interpretation of Boxplots•7分钟
- Laying out multiple plots on a page•8分钟
- Module 5 Summary•1分钟
1个作业•总计30分钟
- Step 2: Self-Check Mutiple-view plots including histogram, boxplots and scatter plot with data provided•30分钟
1个编程作业•总计30分钟
- Step 1: Multiple-view plots including histogram, boxplots and scatter plot with data provided •30分钟
1个讨论话题•总计10分钟
- Why Boxplot Could be Used to Detect Outliers•10分钟
1个非评分实验室•总计60分钟
- Plot multiple group boxplots with data provided•60分钟
攻读学位
课程 是 Ball State University提供的以下学位课程的一部分。如果您被录取并注册,您已完成的课程可计入您的学位学习,您的学习进度也可随之转移。
攻读学位
课程 是 Ball State University提供的以下学位课程的一部分。如果您被录取并注册,您已完成的课程可计入您的学位学习,您的学习进度也可随之转移。
Ball State University
Master of Science in Computer Science
学位 · 24 months
Ball State University
Master of Science in Data Science
学位 · 24 months
必须成功申请并注册。资格要求适用。各院校会根据您现有的学分情况,确定完成本课程后可计入学位要求的学分。单击特定课程了解更多信息。
位教师
授课教师评分
我们要求所有学生根据授课教师的教学风格和质量提供对授课教师的反馈。

提供方

提供方

Ball State Online offers more than 110 online programs in high-demand fields and consistently lands in the Top 20 of the U.S. News & World Report “Best Online Programs” and “Best Online Programs for Veterans” national ranking for several of its online bachelor’s and graduate degrees. Ball State focuses on the student experience, placing emphasis on personal attention from faculty and immersive learning.
人们为什么选择 Coursera 来帮助自己实现职业发展

Felipe M.

Jennifer J.

Larry W.

Chaitanya A.
通过在线学位推动您的职业生涯
获取世界一流大学的学位 - 100% 在线
常见问题
To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
更多问题
提供助学金,
¹ 本课程的部分作业采用 AI 评分。对于这些作业,将根据 Coursera 隐私声明使用您的数据。



