I-CERT Lean Six Sigma Black Belt Level 2 Certification
Move Beyond Traditional Black Belt Competence
Course Overview
I-CERT Lean Six Sigma Black Belt Level 2 Certification is an advanced progression qualification designed for professionals who have already achieved Black Belt Level 1 and want to strengthen their expertise in Lean Six Sigma methodologies, statistical analysis, and strategic process improvement. This certification focuses on enhancing analytical depth and improving the ability to manage more complex, high-impact organisational projects.
The course builds on core Black Belt concepts and introduces more advanced tools and techniques, including enhanced DMAIC application, advanced statistical analysis, regression modelling, design of experiments (DOE), multivariate analysis, and predictive performance improvement methods. Learners will also strengthen leadership capabilities to manage cross-functional teams and deliver data-driven solutions for enterprise-level challenges.
This qualification is suitable for experienced professionals working in quality management, operations, engineering, manufacturing, healthcare, IT, finance, logistics, and consultancy roles who have already completed Black Belt Level 1 and are seeking further advancement.
By completing the I-CERT Lean Six Sigma Black Belt Level 2 Certification, Learners will improve their ability to solve complex problems, optimise organisational processes, and lead high-value improvement initiatives. This certification also serves as a strong pathway toward Black Belt Level 3 and Master Black Belt-level expertise in Lean Six Sigma leadership and continuous improvement.
Study Units
The Lean Six Sigma Black Belt Level 2 Certification includes 33 study units over 180–200 hours, providing advanced skills in process optimization, statistical analysis, and project leadership for operational excellence.
Learning Objectives
Upon completing the Lean Six Sigma Black Belt Level 2 Certification, learners will acquire advanced skills in process improvement, statistical analysis, and operational excellence. The learning outcomes aligned with the 33 study units include:
1. Introduction to Six Sigma
- Understand Six Sigma principles and objectives
- Recognize the strategic role of Six Sigma in organizations
- Identify key benefits and applications of Six Sigma
- Develop a foundation for advanced process improvement
2. Six Sigma History and Practical Applications
- Explore the evolution of Six Sigma methodologies
- Examine real-world applications across industries
- Apply best practices to practical scenarios
- Understand global standards in process improvement
3. Process Improvement and Quality Methodologies
- Apply structured process improvement techniques
- Integrate quality management frameworks
- Identify inefficiencies and optimization opportunities
- Develop measurable performance improvement goals
4. Lean Principles and Concepts
- Understand Lean philosophy and waste elimination
- Apply Lean tools to improve process efficiency
- Enhance value stream flow and operational effectiveness
- Foster continuous improvement culture
5. Core Six Sigma Concepts
- Learn key Six Sigma terminology and metrics
- Understand process variation and capability
- Apply data-driven decision-making
- Establish project objectives aligned with business goals
6. Structured Problem-Solving Approaches
- Apply systematic approaches to problem-solving
- Identify root causes and prioritize solutions
- Develop actionable plans for improvement
- Align solutions with strategic objectives
7. Understanding Business Processes
- Map and analyze business processes
- Identify value-adding and non-value-adding activities
- Improve workflow efficiency
- Align process improvements with organizational goals
8. Quality Fundamentals
- Understand quality management principles
- Implement tools to measure and improve quality
- Monitor process performance
- Support continuous improvement initiatives
9. Project Selection and Prioritization
- Select high-impact Six Sigma projects
- Evaluate potential benefits and risks
- Prioritize initiatives based on organizational objectives
- Ensure alignment with strategic goals
10. Six Sigma Team Roles and Collaboration
- Understand roles within Six Sigma teams
- Facilitate effective collaboration
- Lead cross-functional teams
- Manage stakeholder expectations
11. Introduction to DMAIC and DMADV
- Learn the DMAIC and DMADV frameworks
- Apply structured methodologies to projects
- Identify areas for process improvement
- Enhance problem-solving capabilities
12. Define Phase
- Define project goals and scope
- Identify key stakeholders
- Develop project charters
- Establish measurable objectives
13. Measure Phase
- Implement advanced data collection methods
- Measure process performance accurately
- Identify sources of variation
- Prepare data for analysis
14. Analyze Phase
- Conduct root cause analysis
- Use statistical tools to identify process issues
- Prioritize causes for improvement
- Validate findings with data
15. Improve Phase
- Develop and implement solutions
- Optimize processes using Lean Six Sigma tools
- Test improvements for effectiveness
- Ensure alignment with business objectives
16. Control Phase
- Establish control mechanisms
- Maintain improvements over time
- Monitor performance using control charts
- Sustain process excellence
17. Intermediate Graphical Data Analysis
- Visualize data for insights
- Use graphs to detect trends and patterns
- Support decision-making
- Communicate findings effectively
18. Normal Probability Distributions
- Understand and apply normal distribution concepts
- Analyze process performance data
- Identify deviations from expected outcomes
- Make informed improvement decisions
19. Correlation and Regression Analysis
- Identify relationships between variables
- Apply regression for predictive insights
- Use correlation to guide improvements
- Support data-driven decisions
20. Non-Normal Probability Distributions
- Analyze processes with non-normal data
- Apply appropriate statistical tools
- Identify patterns and risks
- Enhance analytical accuracy
21. Hypothesis Testing Fundamentals
- Formulate hypotheses for process improvement
- Conduct tests to validate assumptions
- Interpret results for decision-making
- Support data-driven solutions
22. Sample Size and Data Reliability
- Determine adequate sample sizes
- Ensure data reliability and accuracy
- Apply statistical principles to projects
- Improve confidence in analysis results
23. Advanced Control Charts
- Monitor processes using control charts
- Detect variations and trends
- Maintain process stability
- Support continuous improvement efforts
24. Applying Statistics to Business Through Six Sigma
- Apply statistical methods to business problems
- Analyze data to support improvement decisions
- Evaluate process performance
- Implement evidence-based solutions
25. Introduction to Minitab
- Use Minitab for data analysis
- Apply statistical tools effectively
- Generate reports and insights
- Enhance analytical skills for projects
26. Graphs and Quality Tools in Minitab
- Create visual representations of data
- Apply quality tools for analysis
- Interpret charts for decision-making
- Support project reporting
27. Statistical Analysis Using the Minitab Stat Menu
- Perform advanced statistical analysis
- Use software tools to support data-driven decisions
- Analyze complex datasets
- Identify actionable insights
28. Analysis of Variance (One-Way ANOVA)
- Conduct ANOVA to compare group differences
- Identify significant process factors
- Apply results to optimize processes
- Support project improvement decisions
29. Design of Experiments (DOE)
- Plan experiments to test process changes
- Identify key variables and their effects
- Analyze results for optimization
- Apply DOE to improvement projects
30. Advanced DOE and Factorial Experiments
- Conduct factorial experiments for multiple variables
- Analyze interactions between factors
- Implement data-driven improvements
- Enhance process design effectiveness
31. Brainstorming and Process Improvement Tools
- Use creative problem-solving techniques
- Identify potential solutions and process improvements
- Prioritize ideas for implementation
- Support team collaboration
32. Process Mapping Techniques
- Map complex processes visually
- Identify bottlenecks and inefficiencies
- Improve workflow and resource utilization
- Align processes with organizational goals
33. Value Stream Mapping
- Apply value stream mapping to optimize processes
- Identify waste and non-value-added activities
- Enhance process flow and efficiency
- Support enterprise-wide Lean initiatives
Ideal Learner
The I-CERT Lean Six Sigma Black Belt Level 2 Certification is designed for experienced Lean Six Sigma professionals who have already completed Black Belt Level 1 and are ready to advance their analytical and leadership capabilities.
This course is ideal for:
• Professionals who have completed Black Belt Level 1 and want to progress further.
• Quality managers and improvement specialists handling complex process challenges.
• Senior engineers, analysts, and operations professionals working with advanced data-driven systems.
• Project leaders responsible for cross-functional and high-impact improvement initiatives.
• Consultants working in operational excellence and business transformation.
• Professionals involved in enterprise-level quality and performance improvement programmes.
• Individuals preparing for Black Belt Level 3 or Master Black Belt progression.
• Professionals across manufacturing, healthcare, IT, finance, logistics, and service industries.
This certification is suitable for Learners who want to strengthen their Black Belt expertise and take on more advanced responsibilities in process optimisation, analytics, and organisational improvement.
Course Details
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Course Eligibility
Learners should meet the following entry requirements:
Course Fee
75k PKR / 230 GBP / 310 USD