Design, Develop and Improve Products and Processes. Be able to apply modern experimental techniques to improve existing products and processes and bring new products and processes to market faster
Learn in-demand skills from university and industry experts
Master a subject or tool with hands-on projects
Develop a deep understanding of key concepts
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Specialization - 4 course series
Learn modern experimental strategy, including factorial and fractional factorial experimental designs, designs for screening many factors, designs for optimization experiments, and designs for complex experiments such as those with hard-to-change factors and unusual responses. There is thorough coverage of modern data analysis techniques for experimental design, including software. Applications include electronics and semiconductors, automotive and aerospace, chemical and process industries, pharmaceutical and bio-pharm, medical devices, and many others.
Participants will complete a project that is typically based around their own work environment, and can use this to effectively demonstrate the application of experimental design methodology. The structure of the course and the step-by-stem process taught in the course is designed to ensure participant success.
Arizona State University has developed a new model for the American Research University, creating an institution that is committed to excellence, access and impact. ASU measures itself by those it includes, not by those it excludes. ASU pursues research that contributes to the public good, and ASU assumes major responsibility for the economic, social and cultural vitality of the communities that surround it.
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There are 15 modules, spread across 4 courses. Each module is based on one chapter of the textbook. The specialization can be completed in approximately 4 months.
Knowledge of basic statistical methods, although the background knowledge is introduced and reviewed throughout the course as needed.
It is not necessary to take the courses in a specific order, but we recommend taking the courses in the order presented, as each subsequent course will build on material from previous courses.
Coursera courses and certificates don't carry university credit, though some universities may choose to accept them for credit.
Design efficient and effective experiments to solve a wide variety of problems in science, engineering, and business where data collection and analysis is essential to success.
This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.
Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate, or you can audit it to view the course materials for free. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. If you only want to read and view the course content, you can audit the course for free. If you cannot afford the fee, you can apply for financial aid.