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Free Six Sigma Certification Course, Technical University of Munich

The Technical University of Munich (TUM) is offering opne online course on Fundamentals of Six Sigma: Quality Engineering and Management. The course will enable you to immediately understand and apply quality concepts in your work and research.

This ten week course cover the fundamentals for quality engineering and management, including the statistics at a Six-Sigma Green Belt level applied to the DMAIC (Define, Measure, Analyze, Improve, Control) process-improvement cycle. The course will start on June 15, 2016

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Course At A Glance

Length: 10 weeks
Effort: 3-4 hours per week
Subject: Business & Management
Institution: Technical University of Munich (TUM) and edX
Price: Free
Certificate Available: Yes. Add a Verified Certificate for $49
Session: Course starts on June 15, 2016

Providers’ Details

Technical University of Munich (TUM) ranks as one of Europe’s leading universities. It placed first among German universities in the International Shanghai Ranking, in both 2011 and 2012, and is one of the few to hold the title of Excellence University. Our researchers are committed to finding solutions to the major challenges facing society: health & nutrition, energy & natural resources, environment & climate, information & communication, mobility & infrastructure.

About This Course

Since the introduction of mass production, the concept of “quality” has evolved from simple assembly line inspections to a broad approach to production and management involving an entire corporation. Quality has become a critical driver for long-term success through continuous process improvement and customer satisfaction. Quality Management today concerns the entire value chain, encompassing multi-tiered supplier networks and customer service and returns.

This business and management course balances the quantitative elements of quality engineering with a managerial approach to using quality in an organization to effect change. We cover the statistical basics needed for a Six-Sigma Green Belt certification, following the well-known process-improvement cycle: Define, Measure, Analyze, Improve, and Control. The most important quality methods and techniques are taught, including sampling, statistical process control, process capability, regression analysis, and design of experiments. Quality management is examined, from the viewpoint of quality incorporated into product design, measuring and controlling quality in production and improving quality, using interactive, guided projects and case studies. The course closes with the presentation of a full Six-Sigma project.

Why Take This Course?

-Quality issues appear everywhere and affect the entire organisation.
-You’ll quickly master quality concepts so that you can apply quality tools and drive quality programs within your own organisation.
-You’ll gain the fundamentals for a Six-Sigma Green Belt in a manageable and positive learning environment, along with the chance to discuss with staff and fellow learners worldwide.

Learning Outcomes

-The fundamentals for quality engineering and management
-The statistical basics at the Six-Sigma Green Belt level
-How to apply the DMAIC process-improvement cycle to your work and research

Instructors

Martin Grunow

Martin Grunow is a professor of production and supply chain management at Technische Universität München and an adjunct professor at Technical University Denmark.

Holly Ott

Holly Ott is a senior lecturer in operations management at Technische Universität München and professor of engineering and business at the Bavarian University of Applied Sciences and Management (Hochschule der Bayerischen Wirtschaft), and an adjunct professor in operations management at Singapore Management University.

Requirements

This course reviews basic statistics and applies them to quality problems and methods. Therefore, basic math skills are necessary.

How To Join This Course

-Go to the course website link
-Create an edX account to SignUp
-Choose “Register Now” to get started.
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Detailed Information