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Data Visualization

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.

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What's inside

Syllabus

Course Orientation

You will become familiar with the course, your classmates, and our learning environment. The orientation will also help you obtain the technical skills required for the course.

Week 1: The Computer and the Human

In this week's module, you will learn what data visualization is, how it's used, and how computers display information. You'll also explore different types of visualization and how humans perceive information.

Week 2: Visualization of Numerical Data

In this week's module, you will start to think about how to visualize data effectively. This will include assigning data to appropriate chart elements, using glyphs, parallel coordinates, and streamgraphs, as well as implementing principles of design and color to make your visualizations more engaging and effective.

Week 3: Visualization of Non-Numerical Data

In this week's module, you will learn how to visualize graphs that depict relationships between data items. You'll also plot data using coordinates that are not specifically provided by the data set.

Week 4: The Visualization Dashboard

In this week's module, you will start to put together everything you've learned by designing your own visualization system for large datasets and dashboards. You'll create and interpret the visualization you created from your data set, and you'll also apply techniques from user-interface design to create an effective visualization system.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Examines data visualization, including techniques, which is standard in industry

Explores pattern discovery in data mining, which is useful for many fields

Provides hands-on methods for practicing pattern discovery methods

Taught by John C. Hart, who is recognized for their work in data mining

Requires students to have some background knowledge in data mining

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Reviews summary

Visually engaging data exploration

Learners say that Data Visualization is an engaging course that provides a strong introduction to data visualization techniques, with a focus on human perception and effective design principles. Students particularly appreciate the well-explained lectures and the relevant assignments, which allow them to apply their new skills in a practical setting. While some learners find the course to be a bit theoretical and would have preferred more hands-on programming, overall, the course is highly recommended for those who want to build a solid foundation in data visualization.

The course instructor provides clear and engaging lectures that make the material easy to understand.

"The classes were great. They are very theoretical in subjects related to computer graphics, I expected something a little more practical. But it was relevant for me, anyway."

"I thought the course was presented very well and that the content was very interesting! I enjoyed the videos that were presented by the instructor and look forward to learning more in the future."

The course provides a strong foundation in human perception and how it relates to data visualization.

"It encourage learner to explore more about data visualization while providing examples and programs to finished the course. However, I found it's quite theoretical and short. "

"give us big picture of visualizations and share lots of practical skills. also cover some mechanisms of why visualization through introducing human visual perception system."

Students find the assignments to be engaging and helpful in applying their new skills.

"The assignments in the course made it a engaging experience."

Students who do not have a programming background may find it challenging to complete the assignments.

"Need to add more materials about software to be used. I used Python libraries, otherwise, I would not able to complete the course."

"It may be a little bit difficult for beginners who cannot program like me."

While the course provides a strong theoretical foundation, some learners would have preferred more hands-on programming practice.

"This course went from accessible to far too technical for someone without programming experience. In order to complete assignments knowledge of programming is needed."

"The course was simply a theoretical overwiew of some basic techniques used in data visualization. The only practical experience was given in the two homeworks, which mostly required to rely on previous or self-taught knowledge and experience."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Data Visualization with these activities:

Review basic probability and statistics concepts

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Having a strong foundation in probability and statistics will help you succeed in this course.

Browse courses on Probability

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Review your notes from a previous probability and statistics course.
Take an online refresher course.
Solve practice problems.

Find a mentor who can provide guidance on data mining

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Having a mentor can provide you with valuable advice and support as you learn about data mining.

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Identify potential mentors.
Reach out to your potential mentors and introduce yourself.
Ask your mentors for guidance and support.

Compile a study guide for the course

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Having a study guide will help you stay organized and prepare for exams.

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Gather your notes, assignments, and quizzes.
Organize your materials into a logical order.
Create a study schedule.

Five other activities

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Mentor a fellow student in the course

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Mentoring a fellow student will help you solidify your understanding of the course material and develop your leadership skills.

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Identify a student who you can mentor.
Meet with your mentee regularly to discuss the course material.
Provide guidance and support to your mentee.

Read Data Mining: Concepts and Techniques, 2nd Edition

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This book provides a comprehensive overview of data mining concepts and techniques, giving you a strong foundation for the course.

View Data Mining: Concepts and Techniques on Amazon

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Read the introduction and first three chapters.
Complete the exercises at the end of each chapter.
Summarize the key concepts in each chapter.

Complete the Data Mining with Python tutorial series

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This tutorial series will help you learn how to use Python for data mining tasks, which will be useful for the programming assignments in the course.

Browse courses on Data Mining

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Watch the videos in the tutorial series.
Complete the practice exercises.
Build a small data mining project using Python.

Practice solving data mining problems on LeetCode

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Solving data mining problems on LeetCode will help you develop your problem-solving skills and improve your understanding of data mining algorithms.

Browse courses on Data Mining

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Choose a set of data mining problems to solve.
Solve the problems using the techniques you learned in the course.
Review your solutions and identify areas where you can improve.

Build a data mining dashboard

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Building a data mining dashboard will help you apply the concepts you learn in the course to a real-world problem, which will reinforce your learning.

Browse courses on Data Mining

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Identify a dataset that you want to analyze.
Choose a data mining algorithm to use for your analysis.
Build a data mining model.
Create a dashboard to visualize your results.

Career center

Learners who complete Data Visualization will develop knowledge and skills that may be useful to these careers:

Data Scientist

Data Scientists are responsible for developing and applying statistical and machine learning methods to analyze and interpret data. They use this information to solve problems and make predictions. Data Visualization is a key skill for Data Scientists, as it allows them to communicate their findings in a clear and concise way.

See salaries and explore the career path for Data Scientist

Statistician

Statisticians are responsible for collecting, analyzing, and interpreting data. They use their knowledge of statistics and data visualization to draw conclusions and make predictions. This course, Data Visualization, can help individuals in this role to create visualizations that are both informative and visually appealing.

See salaries and explore the career path for Statistician

Data Journalist

Data Journalists are responsible for using data to tell stories. They use their knowledge of journalism and data visualization to create visualizations that are both informative and visually appealing. This course, Data Visualization, can help individuals in this role to create visualizations that are both informative and visually appealing.

See salaries and explore the career path for Data Journalist

Market Researcher

Market Researchers are responsible for conducting research to understand market trends and customer behavior. They use this information to develop marketing strategies and products. Data Visualization is a valuable skill for Market Researchers, as it allows them to present their findings in a way that is easy to understand and actionable.

See salaries and explore the career path for Market Researcher

User Experience (UX) Designer

UX Designers are responsible for designing and evaluating the user experience of websites and other digital products. They use their knowledge of human behavior and data visualization to create products that are easy to use and enjoyable. Data Visualization is a valuable skill for UX Designers, as it allows them to create visualizations that communicate information clearly and effectively.

See salaries and explore the career path for User Experience (UX) Designer

Product Designer

Product Designers are responsible for designing and developing new products. They use their knowledge of user experience and data visualization to create products that are both useful and desirable. Data Visualization is a valuable skill for Product Designers, as it allows them to create visualizations that communicate the value and benefits of their products.

See salaries and explore the career path for Product Designer

Information Architect

Information Architects are responsible for designing and organizing the structure and content of websites and other digital products. They use their knowledge of user experience and data visualization to create intuitive and engaging experiences. This course, Data Visualization, can help individuals in this role to create visualizations that are both informative and visually appealing.

See salaries and explore the career path for Information Architect

Data Analyst

Data Analysts examine and interpret data to draw conclusions and make recommendations for decision-making in business and government. This course, Data Visualization, can be useful in this role, as it introduces the principles and techniques of data visualization, which is an essential skill for communicating data-driven insights to stakeholders.

See salaries and explore the career path for Data Analyst

Financial Analyst

Financial Analysts are responsible for analyzing financial data to make investment recommendations. They use their knowledge of finance and data visualization to create visualizations that are both informative and visually appealing. This course, Data Visualization, can help individuals in this role to create visualizations that are both informative and visually appealing.

See salaries and explore the career path for Financial Analyst

Actuary

Actuaries are responsible for assessing risk and uncertainty. They use their knowledge of mathematics and data visualization to create visualizations that are both informative and visually appealing. This course, Data Visualization, can help individuals in this role to create visualizations that are both informative and visually appealing.

See salaries and explore the career path for Actuary

Epidemiologist

Epidemiologists are responsible for studying the causes and distribution of diseases in populations. They use their knowledge of epidemiology and data visualization to identify and track disease outbreaks. This course, Data Visualization, can help individuals in this role to create visualizations that are both informative and visually appealing.

See salaries and explore the career path for Epidemiologist

Software Engineer

Software Engineers are responsible for designing, developing, and maintaining software applications. They use their knowledge of programming languages and data visualization to create software that is both efficient and user-friendly. This course, Data Visualization, can help individuals in this role to create visualizations that are both informative and visually appealing.

See salaries and explore the career path for Software Engineer

Graphic designer

Graphic Designers are responsible for creating visual content for websites, print, and other media. They use their knowledge of design principles and data visualization to create visuals that are both aesthetically pleasing and informative. This course, Data Visualization, can help individuals in this role to create visualizations that are both visually appealing and effective at communicating data.

See salaries and explore the career path for Graphic designer

Data Engineer

Data Engineers are responsible for designing and building the infrastructure that stores and manages data. They use their knowledge of data management and data visualization to create systems that are both efficient and scalable. This course, Data Visualization, can help individuals in this role to create visualizations that are both informative and visually appealing.

See salaries and explore the career path for Data Engineer

Business Analyst

Business Analysts are responsible for analyzing and interpreting data to identify and solve business problems. They use this information to make recommendations for improving business processes and strategies. This course, Data Visualization, can be useful in this role, as it provides the skills and knowledge needed to communicate data-driven insights effectively.

See salaries and explore the career path for Business Analyst

Reading list

We've selected 14 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Data Visualization.

Fundamentals of Data Visualization

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Provides a comprehensive introduction to the fundamental principles and techniques of data visualization, covering topics such as visual perception, data encoding, and interactive visualization. It is an excellent resource for understanding the theoretical foundations and best practices of data visualization.

Fundamentals of Data Visualization: A Primer on...

Kindle Edition

$$$

Information Visualization

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This classic work on information visualization provides an in-depth exploration of the cognitive and perceptual principles underlying the effective design of visual representations of data. It covers a wide range of topics, including visual perception, data encoding, and interactive visualization.

Data Visualization

What's inside

Syllabus

Good to know

Save this course

Reviews summary

Visually engaging data exploration

Activities

Career center

Reading list

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