I-CERT Lean Six Sigma Green Belt Level 2 Certification
In today’s fast-paced business environment, organizations need skilled professionals who can improve efficiency, reduce waste, and deliver consistent quality. The I-CERT Lean Six Sigma Green Belt Level 2 Certification is designed for learners who want to develop practical expertise in Lean Six Sigma methodologies and contribute to continuous improvement within their organizations. This certification provides a solid understanding of process optimization, quality management, and data-driven problem-solving, helping learners create measurable improvements that support business success.
The course combines the proven principles of Lean and Six Sigma to help learners identify process inefficiencies, eliminate non-value-added activities, and improve overall operational performance. Through practical learning and real-world applications, learners gain the confidence to analyze business processes, solve quality-related challenges, improve customer satisfaction, and implement sustainable improvement strategies. .
The I-CERT Lean Six Sigma Green Belt Level 2 Certification equips learners with the knowledge and skills needed to become valuable contributors to quality improvement initiatives across a wide range of industries. With a strong focus on analytical thinking, teamwork, and continuous improvement, this certification enables learners to support organizational excellence, improve productivity, and deliver lasting business value through structured and effective process improvement practices.
Course Overview
Awarding Body
ICTQual AB
Duration
90 – 110 hours
Study Mode
Online
Assessment
100 MCQs
Study Units
- What Is Six Sigma?
- Six Sigma History and Application
- Other Process Improvement and Quality Methods
- Lean Concepts
- Basic Six Sigma Concepts
- Approaching the Problem
- What is a Process?
- Quality
- Selecting the Right Projects
- Basic Six Sigma Team Management
- Introduction to DMAIC and DMADV
- Define
- Measure
- Analyze
- Improve
- Control
- Intermediate Graphical Analysis
- Normal Probability Distributions
- Correlation and Regression
- Non-Normal Probability Distributions
- Hypothesis Testing
- Sample Size
- Advanced Control Charts
- Applying Statistics to Business Applications Through Six Sigma
Entry Requirements
- Minimum Age: Learners must be 18 years or above.
- Educational Background: A high school diploma or equivalent is required; a background in business, engineering, operations, or quality management is considered beneficial.
- Work Experience: No formal Six Sigma experience is required, although basic understanding of workplace processes or quality systems is helpful.
- Language Proficiency: Learners should have a good command of English to understand course materials, participate in learning activities, and complete assessments effectively.
Who Can Enroll
The I-CERT Lean Six Sigma Green Belt Level 2 Certification is designed for learners who want to build strong capabilities in process improvement, quality management, and operational efficiency. It is suitable for individuals aiming to contribute effectively to continuous improvement initiatives across different industries.
- Learners who want to understand Lean Six Sigma principles and apply them in real workplace situations.
- Quality assurance and quality control staff involved in maintaining and improving standards.
- Operations and production personnel seeking to improve efficiency and reduce process waste.
- Team leaders and supervisors responsible for managing workflow and performance improvement.
- Business improvement and process development professionals working on optimization projects.
- Project team members involved in quality-driven initiatives and organizational change.
- Engineers and technical staff aiming to enhance problem-solving and analytical skills.
- Learners from any industry who want to strengthen their career with Lean Six Sigma expertise.
Course Learning Outcomes
Upon completing the Lean Six Sigma Green Belt Level 2 Certification, learners will gain advanced knowledge and practical skills to drive process improvement and operational excellence. The learning outcomes aligned with the 24 study units include:
1. What Is Six Sigma?
- Understand the fundamentals and purpose of Six Sigma
- Recognize its role in process improvement and quality management
- Identify key concepts and terminology used in Six Sigma
- Explain the benefits of Six Sigma in business operations
2. Six Sigma History and Application
- Understand the historical development of Six Sigma
- Explore real-world applications across industries
- Recognize the impact of Six Sigma on operational efficiency
- Analyze case studies of successful Six Sigma implementation
3. Other Process Improvement and Quality Methods
- Gain awareness of alternative quality and improvement methodologies
- Compare Lean, Kaizen, Total Quality Management (TQM), and other approaches
- Understand their integration with Six Sigma initiatives
- Evaluate when to apply specific methodologies
4. Lean Concepts
- Understand core Lean principles and waste elimination
- Apply Lean tools to improve process efficiency
- Integrate Lean with Six Sigma for continuous improvement
- Identify opportunities to optimize workflows
5. Basic Six Sigma Concepts
- Understand key Six Sigma metrics and terminology
- Learn about process variation and performance measurement
- Apply Six Sigma principles to simple process problems
- Develop a foundation for advanced statistical analysis
6. Approaching the Problem
- Learn structured problem-solving techniques
- Define problems clearly using data and evidence
- Identify root causes systematically
- Develop actionable improvement strategies
7. What is a Process?
- Understand the components and flow of business processes
- Map and analyze processes effectively
- Identify inefficiencies and bottlenecks
- Recognize process inputs and outputs
8. Quality
- Understand quality concepts and standards
- Recognize customer requirements and expectations
- Apply quality measurement tools
- Integrate quality principles into process improvement
9. Selecting the Right Projects
- Learn criteria for identifying high-impact projects
- Evaluate project feasibility and benefits
- Align projects with organizational goals
- Prioritize initiatives for maximum value
10. Basic Six Sigma Team Management
- Understand team roles and responsibilities
- Apply effective team management practices
- Facilitate collaboration in process improvement projects
- Support leadership in Six Sigma initiatives
11. Introduction to DMAIC and DMADV
- Understand DMAIC and DMADV methodologies
- Identify when to use each approach
- Apply frameworks to structure process improvement projects
- Develop project charters and objectives
12. Define
- Clearly define project goals and scope
- Identify key stakeholders and requirements
- Develop process maps and project plans
- Set measurable objectives
13. Measure
- Collect and analyze process data
- Establish baseline performance metrics
- Identify sources of variation
- Use measurement tools to quantify process performance
14. Analyze
- Perform root cause analysis using data-driven methods
- Apply statistical techniques to identify process issues
- Use graphical and analytical tools for decision-making
- Prioritize improvement opportunities
15. Improve
- Design and implement process improvements
- Test solutions and validate results
- Apply Lean tools to optimize workflows
- Ensure improvements align with business objectives
16. Control
- Establish control plans to sustain improvements
- Use control charts and monitoring tools
- Ensure process stability and consistency
- Develop documentation for continuous improvement
17. Intermediate Graphical Analysis
- Apply charts and graphs to interpret process data
- Identify trends, patterns, and anomalies
- Make data-driven decisions
- Communicate findings effectively
18. Normal Probability Distributions
- Understand normal distribution and its applications
- Apply probability concepts to process performance
- Analyze data using statistical tools
- Make informed process improvement decisions
19. Correlation and Regression
- Understand relationships between variables
- Apply regression analysis for predictive insights
- Use correlation to identify process dependencies
- Support data-driven decision-making
20. Non-Normal Probability Distributions
- Identify non-normal data patterns
- Apply statistical methods for non-normal distributions
- Analyze and interpret non-standard process data
- Make reliable improvement recommendations
21. Hypothesis Testing
- Formulate and test hypotheses using statistical methods
- Make decisions based on data analysis
- Evaluate process changes and improvements
- Reduce uncertainty in decision-making
22. Sample Size
- Determine appropriate sample sizes for analysis
- Ensure statistical validity and accuracy
- Apply sampling techniques in process studies
- Support effective measurement and control
23. Advanced Control Charts
- Use advanced control charts for process monitoring
- Detect variation and trends in processes
- Ensure consistent quality and performance
- Support long-term process stability
24. Applying Statistics to Business Applications Through Six Sigma
- Apply statistical methods to solve real-world business problems
- Use data to drive process improvement initiatives
- Translate analysis into actionable business insights
- Demonstrate competency in Lean Six Sigma methodology
