Prepare for a career in the field of Six Sigma, quality, and process improvements to get job-ready in less than 4 months. The three courses in this specialization will prepare you to take the ASQ-Certified Six Sigma Black Belt (CSSBB) exam and help you master the Six Sigma methodology, advanced statistical techniques, and team management skills to identify existing challenges, and perform process improvements.
The first course, Six Sigma for Process Improvement, explains the core principles and tools of Six Sigma, DFSS frameworks, and aligning Lean Six Sigma with organizational objectives. The second course, Leadership and Team Management, focuses on team organization and helps align performance measures within the organization. The last course, Advanced Statistical Analysis and Tools, describes the statistical tools for process improvement, design of experiments (DOE), and Lean methods.
By completing this specialization, you will be able to:
Explain the core principles of the Six Sigma methodology, including the systems and tools used.
Apply advanced statistical tools and techniques in each DMAIC phase for process improvement.
Manage team dynamics and assign roles and responsibilities effectively.
Demonstrate leadership skills in project management and problem-solving.
This specialization best suits employees in process improvement teams with significant experience leading and executing Six Sigma, Lean, or other quality improvement projects.
Übungsprojekt
Each course in this specialization concludes with a hands-on peer-review assignment. This end-term project incorporates the learnings of the entire course and is reviewed by your peers to foster learning and feedback.
The peer-reviewed assignments will help you to:
Gain a comprehensive assessment for your assignment with diverse feedback
Actively learn with a highly engaging process of peer reviews
Gain a collaborative learning experience
The end-term projects are based on:
Six Sigma methodology and DFSS framework
Performance and financial measures
Process analysis and graphical tools, DOE, and statistical process control (SPC)
