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Mihaela Danci
Charts allow any audience to understand a topic and quickly make decisions. This course will teach you how to use chart elements to your advantage while creating visualizations based on various types of data.
Read more
Charts allow any audience to understand a topic and quickly make decisions. This course will teach you how to use chart elements to your advantage while creating visualizations based on various types of data.
Read more
Charts allow any audience to understand a topic and quickly make decisions. This course will teach you how to use chart elements to your advantage while creating visualizations based on various types of data.
In today’s data-driven world, building a chart is extremely easy as there are a large number of tools at your disposal that require minimal technical knowledge. While this is an amazing opportunity, you need to make sure you convey the right message while not misleading the audience. In this course, Implementing Data Visualizations, you’ll learn how to efficiently encode data to redirect audience’s attention towards things that matter. First, you’ll explore all data types you may encounter. Next, you’ll discover how to create the right chart based on your data and context. Finally, you’ll learn how to combine visualization with text and how to color grade in order to highlight insights. When you’re finished with this course, you’ll have the data visualization skills and knowledge needed for communicating information in the clearest and most efficient way.
Register for this course and see more details by visiting:
OpenCourser.com/course/du9g7r/implementing
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What's inside
Syllabus
Course Overview
Choosing an Effective Visual for Your Data
Creating Charts for Different Data Types
Labeling and Annotating Chart Components
Read more
Syllabus
Course Overview
Choosing an Effective Visual for Your Data
Creating Charts for Different Data Types
Labeling and Annotating Chart Components
Read more
Editing the Chart Axis
Applying Color to Chart Components
Assembling Additional Elements
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Develops data visualization skills and knowledge for efficiently communicating information in multiple ways
Explores all data types across multiple industries and fields
Teaches efficient data encoding
Taught by Mihaela Danci, a recognized expert in data visualization
Describes the importance of not misleading audiences with data visualizations
Save this course
Save Implementing Data Visualizations to your list so you can find it easily later:
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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 Implementing Data Visualizations with these
activities:
Seek out mentors who can guide your learning
Show steps
Identify mentors who can provide guidance and support throughout your data visualization learning journey.
Show steps
-
Identify professionals in the field who you admire and respect.
-
Reach out to them and ask if they are willing to mentor you.
-
Meet with your mentor regularly to discuss your progress and get feedback.
Compile a list of data visualization resources
Show steps
Create a curated list of resources, such as books, articles, and online courses, that will help you deepen your understanding of data visualization.
Show steps
-
Search for books, articles, and online courses related to data visualization.
-
Review the resources and select the ones that are most relevant and valuable.
-
Organize the resources into a list or database.
-
Share your list with others.
Review data analysis techniques
Show steps
Build a foundation that will help you grasp advanced data visualization techniques and concepts.
Browse courses on
Data Analysis
Show steps
-
Review probability and statistics concepts.
-
Practice data cleaning and manipulation techniques.
-
Refresh your knowledge of data visualization tools.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Create visualizations for different data types
Show steps
Practice creating visualizations for categorical, numerical, and time series data. This will enhance your ability to choose the appropriate visualization for different types of data.
Show steps
-
Gather data from various sources, such as CSV files or databases.
-
Choose the appropriate visualization type based on the data type and the message you want to convey.
-
Create the visualization using a tool like Tableau or Power BI.
-
Review your visualization and make any necessary adjustments.
Attend industry meetups and conferences
Show steps
Connect with other professionals in the data visualization field to learn about the latest trends and best practices.
Show steps
-
Find industry meetups and conferences in your area.
-
Attend the events and introduce yourself to others.
-
Share your knowledge and ask questions to learn from others.
-
Follow up with the people you meet and build relationships.
Design a data visualization dashboard
Show steps
Create a dashboard that combines multiple visualizations to tell a data-driven story. This will allow you to demonstrate your ability to synthesize information and communicate insights effectively.
Show steps
-
Identify the key metrics and insights you want to convey.
-
Select the appropriate visualizations for each metric.
-
Design the layout of the dashboard, ensuring clarity and readability.
-
Implement the dashboard using a tool like Tableau or Power BI.
-
Share your dashboard with others and gather feedback.
Explore advanced data visualization techniques
Show steps
Learn about advanced data visualization techniques such as interactive visualizations, geospatial visualizations, and machine learning-based visualizations.
Show steps
-
Research different advanced data visualization techniques.
-
Find tutorials or online courses that teach these techniques.
-
Follow the tutorials and practice implementing the techniques.
-
Apply the techniques to your own data visualization projects.
Build a portfolio of data visualization projects
Show steps
Create a portfolio of data visualization projects that showcases your skills and abilities. This will provide you with tangible evidence of your learning and make you more competitive in the job market.
Show steps
-
Identify a data visualization problem that you want to solve.
-
Gather data and clean it.
-
Create visualizations that address the problem.
-
Document your project and share it with others.
Seek out mentors who can guide your learning
Show steps
Identify mentors who can provide guidance and support throughout your data visualization learning journey.
Show steps
Show steps
Show steps
- Identify professionals in the field who you admire and respect.
- Reach out to them and ask if they are willing to mentor you.
- Meet with your mentor regularly to discuss your progress and get feedback.
Compile a list of data visualization resources
Show steps
Create a curated list of resources, such as books, articles, and online courses, that will help you deepen your understanding of data visualization.
Show steps
Show steps
Show steps
- Search for books, articles, and online courses related to data visualization.
- Review the resources and select the ones that are most relevant and valuable.
- Organize the resources into a list or database.
- Share your list with others.
Review data analysis techniques
Show steps
Build a foundation that will help you grasp advanced data visualization techniques and concepts.
Browse courses on
Data Analysis
Show steps
Show steps
Show steps
- Review probability and statistics concepts.
- Practice data cleaning and manipulation techniques.
- Refresh your knowledge of data visualization tools.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Create visualizations for different data types
Show steps
Practice creating visualizations for categorical, numerical, and time series data. This will enhance your ability to choose the appropriate visualization for different types of data.
Show steps
Show steps
Show steps
- Gather data from various sources, such as CSV files or databases.
- Choose the appropriate visualization type based on the data type and the message you want to convey.
- Create the visualization using a tool like Tableau or Power BI.
- Review your visualization and make any necessary adjustments.
Attend industry meetups and conferences
Show steps
Connect with other professionals in the data visualization field to learn about the latest trends and best practices.
Show steps
Show steps
Show steps
- Find industry meetups and conferences in your area.
- Attend the events and introduce yourself to others.
- Share your knowledge and ask questions to learn from others.
- Follow up with the people you meet and build relationships.
Design a data visualization dashboard
Show steps
Create a dashboard that combines multiple visualizations to tell a data-driven story. This will allow you to demonstrate your ability to synthesize information and communicate insights effectively.
Show steps
Show steps
Show steps
- Identify the key metrics and insights you want to convey.
- Select the appropriate visualizations for each metric.
- Design the layout of the dashboard, ensuring clarity and readability.
- Implement the dashboard using a tool like Tableau or Power BI.
- Share your dashboard with others and gather feedback.
Explore advanced data visualization techniques
Show steps
Learn about advanced data visualization techniques such as interactive visualizations, geospatial visualizations, and machine learning-based visualizations.
Show steps
Show steps
Show steps
- Research different advanced data visualization techniques.
- Find tutorials or online courses that teach these techniques.
- Follow the tutorials and practice implementing the techniques.
- Apply the techniques to your own data visualization projects.
Build a portfolio of data visualization projects
Show steps
Create a portfolio of data visualization projects that showcases your skills and abilities. This will provide you with tangible evidence of your learning and make you more competitive in the job market.
Show steps
Show steps
Show steps
- Identify a data visualization problem that you want to solve.
- Gather data and clean it.
- Create visualizations that address the problem.
- Document your project and share it with others.
Career center
Learners who complete Implementing Data Visualizations will develop knowledge and skills
that may be useful to these careers:
Market Research Analyst
Market Research Analyst
Market Research Analysts gather, analyze, and interpret market data to help businesses make informed decisions. This course, Implementing Data Visualizations, may be useful to those who wish to enter this role as it will teach you how to choose the most effective visual for any topic and quickly make decisions. You will also learn how to efficiently encode data to redirect audience's attention towards things that matter.
UX Designer
UX Designer
UX Designers improve the user experience of products and services by making them more intuitive and easier to use. Implementing Data Visualizations may be useful to those who wish to enter this role because it will teach you how to create charts for different data types, label and annotate chart components, edit the chart axis, and apply color to chart components.
Consultant
Consultant
Consultants advise businesses on a variety of topics, including data visualization. Implementing Data Visualizations may be useful in this role as it will help you build a foundation in choosing the most effective visual for your data, creating charts for different data types, labeling and annotating chart components, editing the chart axis, and applying color to chart components.
Information Architect
Information Architect
Information Architects design and organize information to make it easy to find and understand. A course in Implementing Data Visualizations may help professionals in this role learn how to choose an effective visual for their data and assemble additional elements.
Business Intelligence Analyst
Business Intelligence Analyst
Business Intelligence Analysts are responsible for identifying, gathering, and interpreting data that may impact an organization. Implementing Data Visualizations may help build a foundation for a role in this field as it will teach you how to combine visualization with text and how to color grade in order to highlight insights.
Data Analyst
Data Analyst
Data Analysts turn raw data into meaningful insights, unraveling the information to help make informed decisions for an organization. Implementing Data Visualizations may be useful to those who wish to enter this role as it will teach you how to build a foundation in choosing the most effective visual for your data, creating charts for different data types, labeling and annotating chart components, editing the chart axis, and applying color to chart components.
Product Manager
Product Manager
Product Managers are responsible for the development and launch of new products and features. Implementing Data Visualizations may be useful in this role as it will teach you how to create charts for different data types, label and annotate chart components, edit the chart axis, and apply color to chart components.
Data Scientist
Data Scientist
Data Scientists use their knowledge of data analysis and machine learning to solve business problems. Implementing Data Visualizations may be useful in this role as it will help you build a foundation in choosing the most effective visual for your data, creating charts for different data types, and applying color to chart components.
Statistician
Statistician
Statisticians collect, analyze, interpret, and present data. Implementing Data Visualizations may be useful in this role as it will help build a foundation in creating charts for different data types, labeling and annotating chart components, and editing the chart axis.
Data Visualization Analyst
Data Visualization Analyst
Data Visualization Analysts parse data to tell visual stories that are used by everyone from a company's data science team to its marketing department. This course, Implementing Data Visualizations, may be useful to those who wish to enter this role because it will teach you how to use a large number of tools that require minimal technical knowledge. You will also learn how to encode data to redirect an audience's attention towards things that matter, how to create the right chart based on your data and context, and how to apply color to chart components.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers build, deploy, and maintain machine learning models. Implementing Data Visualizations may be useful in this role as it will help you build a foundation in creating charts for different data types and labeling and annotating chart components.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. Implementing Data Visualizations may be useful in this role as it will teach you how to create charts for different data types, label and annotate chart components, edit the chart axis, and apply color to chart components.
Data Engineer
Data Engineer
Data Engineers design, build, and maintain data pipelines and infrastructure. Implementing Data Visualizations may be useful in this role as it will help you build a foundation in creating charts for different data types, labeling and annotating chart components, editing the chart axis, and applying color to chart components.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical methods to analyze data and make predictions. Implementing Data Visualizations may be useful in this role as it will teach you how to create charts for different data types, label and annotate chart components, edit the chart axis, and apply color to chart components.
User Researcher
User Researcher
User Researchers conduct research to understand user needs and behaviors. Implementing Data Visualizations may be useful in this role as it will teach you how to create visualizations based on various types of data.
For more career information including salaries, visit:
OpenCourser.com/course/du9g7r/implementing
Reading list
We've selected nine 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
Implementing Data Visualizations.
Save
Classic work on data visualization. It covers topics such as the principles of data visualization, the different types of data visualizations, and the use of data visualization in different fields. It great resource for anyone who wants to learn more about the theory and practice of data visualization.
Serves as a solid foundation for data visualization, covering both theoretical concepts and practical techniques. It provides a comprehensive overview of the field, making it suitable as a core text for introductory courses or as a reference for professionals.
Provides a practical approach to visualizing data, by explaining the types of charts and graphs that are most appropriate for displaying different types of data and how to use these charts effectively to communicate information.
Save
Provides a comprehensive overview of data visualization principles and techniques, covering topics such as choosing the right chart type, using color effectively, and creating clear and concise visualizations. It great resource for anyone who wants to learn more about data visualization or improve their skills in this area.
Save
Covers all aspects of data visualization, from the basics to more advanced techniques, and provides valuable tips and tricks for creating a visually appealing and effective presentation.
Provides a practical guide to data visualization using Python and JavaScript. It covers topics such as data exploration, creating different types of charts, and using libraries such as Matplotlib and Seaborn. It great resource for anyone who wants to learn how to use Python and JavaScript for data visualization.
Offers a unique perspective on data visualization by emphasizing storytelling techniques to make data more engaging and persuasive. It teaches how to craft a compelling narrative using data and create visualizations that resonate with audiences.
Save
Provides a collection of essays on data visualization, covering topics such as the history of data visualization, the principles of effective data visualization, and the use of data visualization in different fields. It great resource for anyone who wants to learn more about the theory and practice of data visualization.
Save
Provides a comprehensive guide to designing effective information dashboards. It covers topics such as the principles of dashboard design, the different types of dashboards, and the use of data visualization in dashboards. It great resource for anyone who wants to learn more about how to design and use dashboards.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/du9g7r/implementing
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Time
140 hours
Level
Intermediate
Via
Pluralsight
Instructor
Mihaela Danci
Language
English
Good to know
Develops data visualization skills and knowledge for efficiently communicating information in multiple ways
Explores all data types across multiple industries and fields
Teaches efficient data encoding
Taught by Mihaela Danci, a recognized expert in data visualization
Describes the importance of not misleading audiences with data visualizations
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