Course Summary
Learn the art of data visualization with this comprehensive course from Coursera. Discover how to create effective visualizations and tell compelling stories with your data.Key Learning Points
- Understand the principles of data visualization and how to create effective visualizations
- Learn how to use tools like Tableau and D3.js to create stunning visualizations
- Discover best practices for creating compelling stories with your data
Related Topics for further study
Learning Outcomes
- Gain a deep understanding of the principles of data visualization
- Develop the skills needed to create effective visualizations using tools like Tableau and D3.js
- Learn best practices for creating compelling stories with your data
Prerequisites or good to have knowledge before taking this course
- Basic knowledge of statistics and data analysis
- Familiarity with a programming language like Python or R
Course Difficulty Level
IntermediateCourse Format
- Online
- Self-paced
Similar Courses
- Python Data Visualization with Matplotlib and Seaborn
- Data Visualization with GGplot2
- Visualizing Data with Python
Related Education Paths
Related Books
Description
Learn the general concepts of data mining along with basic methodologies and applications. Then dive into one subfield in data mining: pattern discovery. Learn in-depth concepts, methods, and applications of pattern discovery in data mining. We will also introduce methods for pattern-based classification and some interesting applications of pattern discovery. This course provides you the opportunity to learn skills and content to practice and engage in scalable pattern discovery methods on massive transactional data, discuss pattern evaluation measures, and study methods for mining diverse kinds of patterns, sequential patterns, and sub-graph patterns.
Outline
- Course Orientation
- Welcome to Data Visualization!
- Syllabus
- About the Discussion Forums
- Updating Your Profile
- Social Media
- Resources
- Orientation Quiz
- Week 1: The Computer and the Human
- Week 1 Introduction
- 1.1.1. Some Books on Data Visualization
- 1.1.2. Overview of Visualization
- 1.2.1. 2-D Graphics
- SVG-example
- 1.2.2. 2-D Drawing
- 1.2.3. 3-D Graphics
- 1.2.4. Photorealism
- 1.2.5. Non-Photorealism
- 1.3.1. The Human
- 1.3.2. Memory
- 1.3.3. Reasoning
- 1.3.4. The Human Retina
- 1.3.5. Perceiving Two Dimensions
- 1.3.6. Perceiving Perspective
- Week 1 Overview
- How the Programming Assignments Work
- Week 1 Quiz
- Week 2: Visualization of Numerical Data
- Week 2 Introduction
- 2.1.1. Data
- 2.1.2. Mapping
- 2.1.3. Charts
- 2.2.1. Glyphs (Part 1)
- 2.2.1. Glyphs (Part 2)
- 2.2.2. Parallel Coordinates
- 2.2.3. Stacked Graphs (Part 1)
- 2.2.3. Stacked Graphs (Part 2)
- 2.3.1. Tufte's Design Rules
- 2.3.2. Using Color
- Week 2 Overview
- Programming Assignment 1: Visualize Data Using a Chart
- Programming Assignment 1 Rubric
- Week 3: Visualization of Non-Numerical Data
- Week 3 Introduction
- 3.1.1. Graphs and Networks
- 3.1.2. Embedding Planar Graphs
- 3.1.3. Graph Visualization
- 3.1.4. Tree Maps
- 3.2.1. Principal Component Analysis
- 3.2.2. Multidimensional Scaling
- 3.3.1. Packing
- Week 3 Overview
- Programming Assignment 2: Visualize Network Data
- Programming Assignment 2 Rubric
- Week 4: The Visualization Dashboard
- Week 4 Introduction
- 4.1.1. Visualization Systems
- 4.1.2. The Information Visualization Mantra: Part 1
- 4.1.2. The Information Visualization Mantra: Part 2
- 4.1.2. The Information Visualization Mantra: Part 3
- 4.1.3. Database Visualization Part: 1
- 4.1.3. Database Visualization Part: 2
- 4.1.3. Database Visualization Part: 3
- 4.2.1. Visualization System Design
- Week 4 Overview
- Week 4 Quiz
Summary of User Reviews
This course on data visualization has received positive reviews from users. Many have praised the course for its comprehensive content and engaging approach. Users have also mentioned the course's usefulness in improving their data visualization skills.Key Aspect Users Liked About This Course
The course's comprehensive content and engaging approach have been praised by many users.Pros from User Reviews
- Comprehensive content that covers various aspects of data visualization
- Engaging approach that makes the course enjoyable and easy to follow
- Useful in improving data visualization skills
- Expert instructors who provide support and guidance throughout the course
Cons from User Reviews
- Some users found the course to be too basic and not challenging enough
- A few users experienced technical issues with the platform
- The course may not be suitable for advanced learners who are looking for more in-depth knowledge
- Some users felt that the course lacked practical exercises and real-world examples
- A few users found the course to be too time-consuming
John C. Hart
4.5 Raiting
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