Course Summary
Learn how to create impactful data visualizations that effectively communicate insights using Tableau and other data visualization tools.Key Learning Points
- Understand the importance of data visualization in communicating insights
- Learn how to choose the right visualization for your data
- Get hands-on experience with Tableau and other popular data visualization tools
Job Positions & Salaries of people who have taken this course might have
- USA: $60,000 - $100,000
- India: ₹5,00,000 - ₹10,00,000
- Spain: €25,000 - €45,000
- USA: $60,000 - $100,000
- India: ₹5,00,000 - ₹10,00,000
- Spain: €25,000 - €45,000
- USA: $70,000 - $120,000
- India: ₹6,00,000 - ₹12,00,000
- Spain: €30,000 - €50,000
- USA: $60,000 - $100,000
- India: ₹5,00,000 - ₹10,00,000
- Spain: €25,000 - €45,000
- USA: $70,000 - $120,000
- India: ₹6,00,000 - ₹12,00,000
- Spain: €30,000 - €50,000
- USA: $80,000 - $130,000
- India: ₹7,00,000 - ₹14,00,000
- Spain: €35,000 - €55,000
Related Topics for further study
Learning Outcomes
- Create impactful data visualizations that effectively communicate insights
- Understand how to choose the right visualization for your data
- Gain hands-on experience with Tableau and other popular data visualization tools
Prerequisites or good to have knowledge before taking this course
- Basic knowledge of data analysis
- Access to Tableau or other data visualization tools
Course Difficulty Level
IntermediateCourse Format
- Online self-paced course
- Video lectures
- Hands-on projects
Similar Courses
- Data Visualization for Everyone
- Data Visualization with Python
Related Education Paths
Notable People in This Field
- Edward Tufte
- Nathan Yau
Related Books
Description
Whether being used to customize advertising to millions of website visitors or streamline inventory ordering at a small restaurant, data is becoming more integral to success. Too often, we’re not sure how use data to find answers to the questions that will make us more successful in what we do. In this course, you will discover what data is and think about what questions you have that can be answered by the data – even if you’ve never thought about data before. Based on existing data, you will learn to develop a research question, describe the variables and their relationships, calculate basic statistics, and present your results clearly. By the end of the course, you will be able to use powerful data analysis tools – either SAS or Python – to manage and visualize your data, including how to deal with missing data, variable groups, and graphs. Throughout the course, you will share your progress with others to gain valuable feedback, while also learning how your peers use data to answer their own questions.
Outline
- Selecting a research question
- Welcome Video
- Video Lesson - Steps in data analysis
- Video Lesson - What do we mean by data?
- Video Lesson - Datasets and codebooks
- Video Lesson - Developing a research question
- Course codebooks
- Course Data Sets
- Getting Set Up for the Assignments
- Tumblr Instructions
- Troubleshooting Your Tumblr Assignment Blog Link
- Writing your first program - SAS or Python
- SAS Lesson 1 - Defining exploratory data analysis
- SAS Lesson 2 - SAS coding conventions
- SAS Lesson 3 - Running your program and examining frequency distribution
- SAS Lesson 4 - Refining your research question by selecting rows
- Python Lesson 1 - Defining Exploratory Data Analysis
- Python Lesson 2 - Python Coding Conventions
- Python Lesson 3 - Running your program and examining frequency distributions
- Python Lesson 4 - Refining your research question by selecting rows
- Choosing SAS or Python
- Getting Started with SAS
- Getting Started with Python
- Codebook for Video Examples
- SAS Program for Video Examples
- Python Program for Video Examples
- Uploading Your Own Data to SAS
- Assignment Sample
- Managing Data
- SAS Lesson 1 - Setting aside missing data
- SAS Lesson 2 - Coding in valid data and recoding values
- SAS Lesson 3 - Creating secondary variables
- SAS Lesson 4 - Grouping variables within individual variables
- Python Lesson 1 - Setting aside missing data
- Python Lesson 2 - Coding valid data and recoding values
- Python Lesson 3 - Creating secondary variables
- Python Lesson 4 - Grouping values within individual variables
- SAS Program for Video Examples
- Python Program for Video Examples
- Codebook for Video Examples
- Assignment Sample
- Visualizing Data
- SAS Lesson 1 - Graphing individual variables
- SAS Lesson 2 - Describing distributions visually
- SAS Lesson 3 - Measures of center and spread
- SAS Lesson 4 - Designing the role each of your variables will play
- SAS Lesson 5 - Graphing decisions: categorical response variables
- SAS Lesson 6 - Graphing decisions: quantitative response variable
- Python Lesson 1 - Graphing individual variables
- Python Lesson 2 - Describing distributions visually
- Python Lesson 3 - Measures of Center and Spread
- Python Lesson 4 - Designing the role each of your variables will play
- Python Lesson 5 - Graphing Decisions: Categorical response variables
- Python Lesson 6 - Graphing decisions: quantitative response variable
- Graphing Decisions Flowchart
- SAS Programs for Video Examples
- Python Programs for Video Examples
- Codebooks for Video Examples
- Assignment Sample
- Supplemental Materials (All Weeks)
- How to Write a Literature Review
- Translation Code
- Acknowledgments
Summary of User Reviews
Discover the art of data visualization with this course on Coursera. See what users are saying about this course, including its overall rating and one key aspect that many users thought was good.Key Aspect Users Liked About This Course
Many users appreciated the hands-on approach to learning data visualization, which helped them gain practical skills.Pros from User Reviews
- The course provides a comprehensive overview of data visualization, covering everything from basic concepts to advanced techniques.
- The instructors are knowledgeable, engaging, and responsive to student questions and feedback.
- The course offers plenty of opportunities to practice data visualization skills through exercises and projects.
- The course is well-structured and easy to follow, making it accessible to beginners and intermediate learners alike.
Cons from User Reviews
- Some users felt that the course could benefit from more in-depth coverage of certain topics.
- A few users found the course to be too focused on theory and not enough on practical applications.
- A handful of users experienced technical difficulties with the course platform or assignments.
- A few users felt that the course was overpriced compared to other data visualization courses available online.
Lisa Dierker
4.4 Raiting
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