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Data Visualization for Developers
Dan Appleman
Dan Appleman
This course covers the fundamentals of data visualization that every developer needs to know regardless of architecture, platform, tools, or language.
Read more
This course covers the fundamentals of data visualization that every developer needs to know regardless of architecture, platform, tools, or language.
Read more
This course covers the fundamentals of data visualization that every developer needs to know regardless of architecture, platform, tools, or language.
At some point in your software development career, you may be called upon to produce a graph or a chart. Delivering on even a simple request can be remarkably complex. How much data is there and where does it live? What kind of chart should you use? Should the chart be rendered on a server or on the client? What kind of clients should you support, and what are the consequences of that choice? This course introduces every aspect of visualization, from story, to numbers, to architecture, to code.
Register for this course and see more details by visiting:
OpenCourser.com/course/ep5gqr/data
What's inside
Syllabus
Introduction
Charting - 1A
Business Intelligence
Visualization Architecture
Read more
Syllabus
Introduction
Charting - 1A
Business Intelligence
Visualization Architecture
Read more
Hands-On Visualization
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Develops data visualization skills, which help developers convey information effectively
Taught by Dan Appleman, who are recognized for their work in data visualization
Explores data visualization concepts, which are standard in software development
Covers visualization architecture, which is essential for designing effective data visualizations
Provides hands-on experience with data visualization, which is crucial for practical implementation
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Activities
Coming soon
We're preparing activities for
Data Visualization for Developers.
These are activities you can do either before, during, or after a course.
Career center
Learners who complete Data Visualization for Developers will develop knowledge and skills
that may be useful to these careers:
Data Visualization Developer
Data Visualization Developer
The Data Visualization Developer creates interactive data visualizations to help users understand complex data. Taking this course will introduce you to the fundamentals of data visualization, including the different types of charts and graphs, the principles of design, and the use of color and typography.
Marketing Analyst
Marketing Analyst
The Marketing Analyst is responsible for collecting, analyzing, and interpreting data to support marketing campaigns. They use data visualization techniques to communicate their findings to stakeholders, so this course can help develop your skills in this area.
Front-End Developer
Front-End Developer
The Front-End Developer is responsible for the design and development of the user interface of a website or application. Data visualization is often prominent in user interfaces, so this course can help deepen your skills in that area.
Business Intelligence Analyst
Business Intelligence Analyst
The Business Intelligence Analyst is responsible for collecting, analyzing, and interpreting data to support decision-making. They use data visualization techniques to communicate their findings to stakeholders, so this course can help develop skills in this area.
Machine Learning Engineer
Machine Learning Engineer
The Machine Learning Engineer is responsible for the design, development, and maintenance of machine learning models. They often use data visualization techniques to debug and profile their models, so this course may be helpful in developing these skills.
Data Engineer
Data Engineer
The Data Engineer is responsible for the design, development, and maintenance of data pipelines. They use data visualization techniques to understand the flow of data through their pipelines, so this course may be helpful in building a foundation in this area.
Data Architect
Data Architect
The Data Architect is responsible for the design and maintenance of the data architecture of an organization. Taking this course would help in deepening your understanding of data visualization and how it fits into the larger data architecture of an organization.
Financial Analyst
Financial Analyst
The Financial Analyst is responsible for evaluating and making recommendations on investments. They use data visualization techniques to analyze financial data and make investment decisions, so this course may be helpful in building a foundation in this area.
Data Scientist
Data Scientist
The Data Scientist is responsible for using data to solve business problems. They have a deep understanding of data analysis and visualization, so this course may be helpful in developing these skills.
User Experience (UX) Designer
User Experience (UX) Designer
The UX Designer is responsible for the design of the user experience of a website or application. They use data visualization techniques to understand how users interact with a product, so this course may be helpful in developing these skills.
Quantitative Analyst (Quant)
Quantitative Analyst (Quant)
The Quantitative Analyst is responsible for using mathematical and statistical models to analyze data and make investment decisions. They often use data visualization techniques to communicate their findings to stakeholders, so this course may be helpful in building a foundation in this area.
Database Administrator (DBA)
Database Administrator (DBA)
The Database Administrator is responsible for the design, development, and maintenance of databases. They use data visualization techniques to understand the performance of their databases, so this course may be helpful in building a foundation in this area.
Software Engineer
Software Engineer
The Software Engineer is responsible for the design, development, and maintenance of software applications. They often use data visualization techniques to debug and profile their code, so this course may be helpful in developing these skills.
Data Science Engineer
Data Science Engineer
The Data Science Engineer is an IT professional who designs, develops, and maintains the infrastructure and tools used for data science. They have a deep understanding of data analysis and visualization, so this course may be helpful in building a foundation in these areas.
Product Manager
Product Manager
The Product Manager is responsible for the development and management of a product. They use data visualization techniques to understand how users interact with a product, so this course may be helpful in building a foundation in this area.
For more career information including salaries, visit:
OpenCourser.com/course/ep5gqr/data
Reading list
We've selected 13 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 for Developers.
Save
This classic book on data visualization provides a comprehensive overview of the principles of data visualization. It covers topics such as data types, chart types, and design principles. It valuable resource for developers who want to learn more about the theory and practice of data visualization.
Provides a practical guide to creating effective data visualizations. It covers topics such as design principles, color theory, and storytelling. It valuable resource for developers who want to create data visualizations that are both informative and visually appealing.
Save
Provides a comprehensive overview of deep learning. It covers topics such as neural networks, convolutional neural networks, and recurrent neural networks. It valuable resource for developers who want to learn more about deep learning and how to use it to solve real-world problems.
Provides a comprehensive overview of reinforcement learning. It covers topics such as Markov decision processes, value functions, and reinforcement learning algorithms. It valuable resource for developers who want to learn more about reinforcement learning and how to use it to solve real-world problems.
Provides a comprehensive overview of natural language processing with Python. It covers topics such as text preprocessing, natural language understanding, and natural language generation. It valuable resource for developers who want to learn more about natural language processing and how to use it to solve real-world problems.
Provides a comprehensive overview of speech and language processing. It covers topics such as speech recognition, natural language understanding, and speech synthesis. It valuable resource for developers who want to learn more about speech and language processing and how to use it to solve real-world problems.
Provides a comprehensive overview of information theory, inference, and learning algorithms. It covers topics such as probability theory, Bayesian inference, and machine learning. It valuable resource for developers who want to learn more about the theoretical foundations of machine learning and how to use them to solve real-world problems.
Provides a comprehensive overview of data science with Python. It covers topics such as data wrangling, machine learning, and data visualization. It valuable resource for developers who want to learn more about data science and how to use Python for data analysis.
Provides a practical guide to creating data visualizations with Python and JavaScript. It covers topics such as data wrangling, chart types, and interactive visualizations. It valuable resource for developers who want to create data visualizations with code.
Provides a practical guide to using ggplot2 for data visualization. It covers topics such as data wrangling, chart types, and interactive visualizations. It valuable resource for developers who want to create data visualizations with R.
Provides a practical guide to using D3.js for data visualization. It covers topics such as data wrangling, chart types, and interactive visualizations. It valuable resource for developers who want to create data visualizations with JavaScript.
Save
Provides a practical guide to using R for data visualization. It covers topics such as data wrangling, chart types, and interactive visualizations. It valuable resource for developers who want to create data visualizations with R.
Save
Provides a practical guide to using Tableau for data visualization. It covers topics such as data preparation, chart types, and dashboard design. It valuable resource for developers who want to use Tableau to create data visualizations.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/ep5gqr/data
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Time
115 hours
Level
Intermediate
Via
Pluralsight
Instructor
Dan Appleman
Language
English
Good to know
Develops data visualization skills, which help developers convey information effectively
Taught by Dan Appleman, who are recognized for their work in data visualization
Explores data visualization concepts, which are standard in software development
Covers visualization architecture, which is essential for designing effective data visualizations
Provides hands-on experience with data visualization, which is crucial for practical implementation
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