Advanced Certificate in Accessible Design Principles: Data-Driven Solutions
-- ViewingNowThe Advanced Certificate in Accessible Design Principles: Data-Driven Solutions is a comprehensive course that emphasizes the importance of designing inclusive digital experiences. This certification equips learners with essential skills to create accessible data visualizations, web applications, and interfaces, ensuring equal access for all users, including those with disabilities.
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⢠Accessible Data Visualization: Utilizing charts, graphs, and infographics in an accessible way is crucial for users with disabilities. This unit will cover best practices for creating and implementing data visualizations that are perceivable, operable, understandable, and robust.
⢠Inclusive Design for Big Data: This unit will cover the principles of inclusive design when working with large datasets. It will include topics such as data collection, analysis, and presentation, with a focus on accessibility and usability for all users.
⢠Accessible Data Tables: Data tables are a common way to present large amounts of data, but they can be difficult for users with disabilities to navigate. This unit will cover best practices for creating accessible data tables, including proper markup, table headers, and summaries.
⢠User Research for Accessible Design: Understanding the needs and preferences of users with disabilities is essential for creating accessible data-driven solutions. This unit will cover best practices for conducting user research with a diverse group of participants, including those with disabilities.
⢠Accessible Machine Learning: Machine learning algorithms and models can be inaccessible to users with disabilities. This unit will cover best practices for creating accessible machine learning models, including data preprocessing, model training, and evaluation.
⢠Accessible Natural Language Processing: Natural language processing (NLP) techniques can be used to extract insights from unstructured data, but they can also be inaccessible to users with disabilities. This unit will cover best practices for creating accessible NLP models, including data preprocessing, model training, and evaluation.
⢠Accessible Geospatial Data: Geospatial data is often presented in the form of maps, but maps can be difficult for users with disabilities to navigate. This unit will cover best practices for creating accessible geospatial data visualizations, including proper markup, alternative text, and user controls.
⢠Accessibility Testing for Data-Driven Solutions: Testing is an essential part of ensuring accessibility for data-driven solutions. This unit will cover best practices for accessibility testing, including automated testing tools, manual testing, and user testing with participants with disabilities.
⢠Accessible Data APIs
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