2996 Courses in Epping

Lean Six Sigma Black Belt Certification Program: In-House Training This course is specifically for people wanting to become Lean Six Sigma Black Belts, who are already Lean Six Sigma practitioners. If advanced statistical analysis is needed to identify root causes and optimal process improvements, (Lean) Six Sigma Green Belts typically ask Black Belts or Master Black Belts to conduct these analyses. This course will change that. Green Belts wanting to advance their statistical abilities will have a considerable amount of hands-on practice in techniques such as Statistical Process Control, MSA, Hypothesis Testing, Correlation and Regression, Design of Experiments, and many others. Participants will also work throughout the course on a real-world improvement project from their own business environment. This provides participants with hands-on learning and provides the organization with an immediate ROI once the project is completed. IIL instructors will provide free project coaching throughout the course. What you Will Learn At the end of this program, you will be able to: Use Minitab for advanced data analysis Develop appropriate sampling strategies Analyze differences between samples using Hypothesis Tests Apply Statistical Process Control to differentiate common cause and special cause variation Explain and apply various process capability metrics Conduct Measurement System Analysis and Gage R&R studies for both discrete and continuous data Conduct and analyze simple and multiple regression analysis Plan, execute, and analyze designed experiments Drive sustainable change efforts through leadership, change management, and stakeholder management Successfully incorporate advanced analysis techniques while moving projects through the DMAIC steps Explain the main concepts of Design for Six Sigma including QFD Introduction: DMAIC Review IIL Black Belt Certification Requirements Review Project Selection Review Define Review Measure Review Analyze Review Improve Review Control Introduction: Minitab Tool Introduction to Minitab Minitab basic statistics and graphs Special features Overview of Minitab menus Introduction: Sampling The Central Limit Theorem Confidence Interval of the mean Sample size for continuous data (mean) Confidence Interval for proportions Sample size for discrete data (proportions) Sampling strategies (review) Appendix: CI and sample size for confidence levels other than 95% Hypothesis Testing: Introduction Why use advanced stat tools? What are hypothesis tests? The seven steps of hypothesis tests P value errors and hypothesis tests Hypothesis Testing: Tests for Averages 1 factor ANOVA and ANOM Main Effect Plots, Interaction Plots, and Multi-Vari Charts 2 factor ANOVA and ANOM Hypothesis Testing: Tests for Standard Deviations Testing for equal variance Testing for normality Choosing the right hypothesis test Hypothesis Testing: Chi Square and Other Hypothesis Test Chi-square test for 1 factor ANOM test for 1 factor Chi-square test for 2 factors Exercise hypothesis tests - shipping Non-parametric tests Analysis: Advanced Control Charts Review of Common Cause and Special Cause Variation Review of the Individuals Control Charts How to calculate Control Limits Four additional tests for Special Causes Control Limits after Process Change Discrete Data Control Charts Control Charts for Discrete Proportion Data Control Charts for Discrete Count Data Control Charts for High Volume Processes with Continuous Data Analysis: Non-Normal Data Test for normal distribution Box-Cox Transformation Box-Cox Transformation for Individuals Control Charts Analysis: Time Series Analysis Introduction to Time Series Analysis Decomposition Smoothing: Moving Average Smoothing: EWMA Analysis: Process Capability Process capability Discrete Data: Defect metrics Discrete Data: Yield metrics Process Capability for Continuous Data: Sigma Value Short- and long-term capabilities Cp, Cpk, Pp, Ppk capability indices Analysis: Measurement System Analysis What is Measurement System Analysis? What defines a good measurement system? Gage R&R Studies Attribute / Discrete Gage R&R Continuous Gage R&R Regression Analysis: Simple Correlation Correlation Coefficient Simple linear regression Checking the fit of the Regression Model Leverage and influence analysis Correlation and regression pitfalls Regression Analysis: Multiple Regression Analysis Introduction to Multiple Regression Multicollinearity Multiple Regression vs. Simple Linear Regression Regression Analysis: Multiple Regression Analysis with Discrete Xs Introduction Creating indicator variables Method 1: Going straight to the intercepts Method 2: Testing for differences in intercepts Logistic Regression: Logistic Regression Introduction to Logistic Regression Logistic Regression - Adding a Discrete X Design of Experiments: Introduction Design of Experiment OFAT experimentation Full factorial design Fractional factorial design DOE road map, hints, and suggestions Design of Experiments: Full Factorial Designs Creating 2k Full Factorial designs in Minitab Randomization Replicates and repetitions Analysis of results: Factorial plots Analysis of results: Factorial design Analysis of results: Fits and Residuals Analysis of results: Response Optimizer Analysis of results: Review Design of Experiments: Pragmatic Approaches Designs with no replication Fractional factorial designs Screening Design of Experiment Case Study Repair Time Blocking Closing: Organizational Change Management Organizational change management Assuring project sponsorship Emphasizing shared need for change Mobilizing stakeholder commitment Closing: Project Management for Lean Six Sigma Introduction to project management Project management for Lean Six Sigma The project baseline plan Work Breakdown Structure (WBS) Resource planning Project budget Project risk Project schedule Project executing Project monitoring and controlling and Closing Closing: Design for Lean Six Sigma Introduction to Design for Lean Six Sigma (DMADV) Introduction to Quality Function Deployment (QFD) Summary and Next Steps IIL's Lean Six Sigma Black Belt Certification Program also prepares you to pass the IASSC Certified Black Belt Exam (optional)

Lean Six Sigma Black Belt Certification Program This course is specifically for people wanting to become Lean Six Sigma Black Belts, who are already Lean Six Sigma practitioners. If advanced statistical analysis is needed to identify root causes and optimal process improvements, (Lean) Six Sigma Green Belts typically ask Black Belts or Master Black Belts to conduct these analyses. This course will change that. Green Belts wanting to advance their statistical abilities will have a considerable amount of hands-on practice in techniques such as Statistical Process Control, MSA, Hypothesis Testing, Correlation and Regression, Design of Experiments, and many others. Participants will also work throughout the course on a real-world improvement project from their own business environment. This provides participants with hands-on learning and provides the organization with an immediate ROI once the project is completed. IIL instructors will provide free project coaching throughout the course. What you Will Learn At the end of this program, you will be able to: Use Minitab for advanced data analysis Develop appropriate sampling strategies Analyze differences between samples using Hypothesis Tests Apply Statistical Process Control to differentiate common cause and special cause variation Explain and apply various process capability metrics Conduct Measurement System Analysis and Gage R&R studies for both discrete and continuous data Conduct and analyze simple and multiple regression analysis Plan, execute, and analyze designed experiments Drive sustainable change efforts through leadership, change management, and stakeholder management Successfully incorporate advanced analysis techniques while moving projects through the DMAIC steps Explain the main concepts of Design for Six Sigma including QFD Introduction: DMAIC Review IIL Black Belt Certification Requirements Review Project Selection Review Define Review Measure Review Analyze Review Improve Review Control Introduction: Minitab Tool Introduction to Minitab Minitab basic statistics and graphs Special features Overview of Minitab menus Introduction: Sampling The Central Limit Theorem Confidence Interval of the mean Sample size for continuous data (mean) Confidence Interval for proportions Sample size for discrete data (proportions) Sampling strategies (review) Appendix: CI and sample size for confidence levels other than 95% Hypothesis Testing: Introduction Why use advanced stat tools? What are hypothesis tests? The seven steps of hypothesis tests P value errors and hypothesis tests Hypothesis Testing: Tests for Averages 1 factor ANOVA and ANOM Main Effect Plots, Interaction Plots, and Multi-Vari Charts 2 factor ANOVA and ANOM Hypothesis Testing: Tests for Standard Deviations Testing for equal variance Testing for normality Choosing the right hypothesis test Hypothesis Testing: Chi Square and Other Hypothesis Test Chi-square test for 1 factor ANOM test for 1 factor Chi-square test for 2 factors Exercise hypothesis tests - shipping Non-parametric tests Analysis: Advanced Control Charts Review of Common Cause and Special Cause Variation Review of the Individuals Control Charts How to calculate Control Limits Four additional tests for Special Causes Control Limits after Process Change Discrete Data Control Charts Control Charts for Discrete Proportion Data Control Charts for Discrete Count Data Control Charts for High Volume Processes with Continuous Data Analysis: Non-Normal Data Test for normal distribution Box-Cox Transformation Box-Cox Transformation for Individuals Control Charts Analysis: Time Series Analysis Introduction to Time Series Analysis Decomposition Smoothing: Moving Average Smoothing: EWMA Analysis: Process Capability Process capability Discrete Data: Defect metrics Discrete Data: Yield metrics Process Capability for Continuous Data: Sigma Value Short- and long-term capabilities Cp, Cpk, Pp, Ppk capability indices Analysis: Measurement System Analysis What is Measurement System Analysis? What defines a good measurement system? Gage R&R Studies Attribute / Discrete Gage R&R Continuous Gage R&R Regression Analysis: Simple Correlation Correlation Coefficient Simple linear regression Checking the fit of the Regression Model Leverage and influence analysis Correlation and regression pitfalls Regression Analysis: Multiple Regression Analysis Introduction to Multiple Regression Multicollinearity Multiple Regression vs. Simple Linear Regression Regression Analysis: Multiple Regression Analysis with Discrete Xs Introduction Creating indicator variables Method 1: Going straight to the intercepts Method 2: Testing for differences in intercepts Logistic Regression: Logistic Regression Introduction to Logistic Regression Logistic Regression - Adding a Discrete X Design of Experiments: Introduction Design of Experiment OFAT experimentation Full factorial design Fractional factorial design DOE road map, hints, and suggestions Design of Experiments: Full Factorial Designs Creating 2k Full Factorial designs in Minitab Randomization Replicates and repetitions Analysis of results: Factorial plots Analysis of results: Factorial design Analysis of results: Fits and Residuals Analysis of results: Response Optimizer Analysis of results: Review Design of Experiments: Pragmatic Approaches Designs with no replication Fractional factorial designs Screening Design of Experiment Case Study Repair Time Blocking Closing: Organizational Change Management Organizational change management Assuring project sponsorship Emphasizing shared need for change Mobilizing stakeholder commitment Closing: Project Management for Lean Six Sigma Introduction to project management Project management for Lean Six Sigma The project baseline plan Work Breakdown Structure (WBS) Resource planning Project budget Project risk Project schedule Project executing Project monitoring and controlling and Closing Closing: Design for Lean Six Sigma Introduction to Design for Lean Six Sigma (DMADV) Introduction to Quality Function Deployment (QFD) Summary and Next Steps IIL's Lean Six Sigma Black Belt Certification Program also prepares you to pass the IASSC Certified Black Belt Exam (optional)

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Lean Six Sigma Green Belt Certification Program This learning series is designed to enable participants to fulfill the important role of a Lean Six Sigma Green Belt and to incorporate the Lean Six Sigma mindset into their leadership skills. Green Belt is not just a role, it is also a competency required for leadership positions at many top companies. This learning series is designed to enable participants to fulfill the important role of a Lean Six Sigma Green Belt and to incorporate the Lean Six Sigma mindset into their leadership skills. With a real-world project focus, the series will teach the fundamental methodology, tools, and techniques of the Define, Measure, Analyze, Improve and Control Process Improvement Methodology. This course is delivered through sixteen 3-hour online sessions. What you Will Learn At the end of this program, you will be able to: Identify strategies for effectively leading high performing process improvement teams Analyze whether projects align with business strategy Apply process improvement methodologies to DMAIC steps, based on real world scenarios Explain ways to appropriately respond to process variation Distinguish among best practice problem solving methodologies Evaluate and effectively communicate data-driven decisions, based on real world scenarios Introduction Lean Six Sigma & quality The vision The methodologies The metric Project Selection Why Projects Random idea generation Targeted idea generation CTQs (Critical to Quality) & projects Project screening criteria Quick improvements Introduction to Define Project Planning Developing the core charter Developing a project charter Facilitation Process Management Business process management Top-down process mapping Voice of the Customer Voice of Customer Stakeholder analysis Communication planning Kicking off the project Define Summary Introduction to Measure Data Collection Fact-based decision making Data sampling Operations definitions Data collection plan Measurement system analysis Graphical Statistics for Continuous Data Meet Six SigmaXL Graphical & statistical tools Data stratification Graphical Statistics for Discrete Data Pareto analysis Dot plots Plotting data over time: Looking for patterns Variation Concepts Variation is reality Special Cause and Common Cause variation Example of standard business reporting Individuals Control Chart Process Capability Genesis of process capability Calculating the metrics of Six Sigma Yield metrics: Measuring process efficiency Cost of Poor Quality The Cost of Poor Quality (COPQ) Cost of Quality categories Calculating the Cost of Poor Quality Measure Summary Introduction to Analyze Process Analysis Introduction to process analysis Value-added analysis Cycle time analysis WIP & pull systems Analyzing bottlenecks and constraints Cause & Effect Analysis Fishbone/Ishikawa diagram 5-Whys analysis Graphical & statistical tools Advanced Analysis Why use hypothesis rests? Hypothesis tests Correlation and regression analysis Analyze Summary Introduction to Improve Solutions Creativity techniques Generating alternative solutions Solution selection techniques Introduction to Design of Experiments Introduction to DOE DOE activity Error Proofing Failure mode & effect analysis Poka-Yoke Project Management Fundamentals Successful teams Project roles Conflict management Standardization Standardization The Visual Workplace 5S Piloting & Verifying Results What is a pilot? Evaluating results Improve Summary Introduction to Control Statistical Process Control Review of Special & Common Cause variation Review of Individual Control Chart P-Chart for discrete proportion data Transition Planning Control plan Project closure Control Summary Summary and Next Steps

Lean Six Sigma Green Belt Certification Program: In-House Training This learning series is designed to enable participants to fulfill the important role of a Lean Six Sigma Green Belt and to incorporate the Lean Six Sigma mindset into their leadership skills. Green Belt is not just a role, it is also a competency required for leadership positions at many top companies. This learning series is designed to enable participants to fulfill the important role of a Lean Six Sigma Green Belt and to incorporate the Lean Six Sigma mindset into their leadership skills. With a real-world project focus, the series will teach the fundamental methodology, tools, and techniques of the Define, Measure, Analyze, Improve and Control Process Improvement Methodology. This course is delivered through sixteen 3-hour online sessions. What you Will Learn At the end of this program, you will be able to: Identify strategies for effectively leading high performing process improvement teams Analyze whether projects align with business strategy Apply process improvement methodologies to DMAIC steps, based on real world scenarios Explain ways to appropriately respond to process variation Distinguish among best practice problem solving methodologies Evaluate and effectively communicate data-driven decisions, based on real world scenarios Introduction Lean Six Sigma & quality The vision The methodologies The metric Project Selection Why Projects Random idea generation Targeted idea generation CTQs (Critical to Quality) & projects Project screening criteria Quick improvements Introduction to Define Project Planning Developing the core charter Developing a project charter Facilitation Process Management Business process management Top-down process mapping Voice of the Customer Voice of Customer Stakeholder analysis Communication planning Kicking off the project Define Summary Introduction to Measure Data Collection Fact-based decision making Data sampling Operations definitions Data collection plan Measurement system analysis Graphical Statistics for Continuous Data Meet Six SigmaXL Graphical & statistical tools Data stratification Graphical Statistics for Discrete Data Pareto analysis Dot plots Plotting data over time: Looking for patterns Variation Concepts Variation is reality Special Cause and Common Cause variation Example of standard business reporting Individuals Control Chart Process Capability Genesis of process capability Calculating the metrics of Six Sigma Yield metrics: Measuring process efficiency Cost of Poor Quality The Cost of Poor Quality (COPQ) Cost of Quality categories Calculating the Cost of Poor Quality Measure Summary Introduction to Analyze Process Analysis Introduction to process analysis Value-added analysis Cycle time analysis WIP & pull systems Analyzing bottlenecks and constraints Cause & Effect Analysis Fishbone/Ishikawa diagram 5-Whys analysis Graphical & statistical tools Advanced Analysis Why use hypothesis rests? Hypothesis tests Correlation and regression analysis Analyze Summary Introduction to Improve Solutions Creativity techniques Generating alternative solutions Solution selection techniques Introduction to Design of Experiments Introduction to DOE DOE activity Error Proofing Failure mode & effect analysis Poka-Yoke Project Management Fundamentals Successful teams Project roles Conflict management Standardization Standardization The Visual Workplace 5S Piloting & Verifying Results What is a pilot? Evaluating results Improve Summary Introduction to Control Statistical Process Control Review of Special & Common Cause variation Review of Individual Control Chart P-Chart for discrete proportion data Transition Planning Control plan Project closure Control Summary Summary and Next Steps

Advanced Junos SP Routing course description This is designed to provide students with detailed coverage of OSPF, IS-IS, BGP, and routing policy. Students will gain experience in configuring, monitoring, and troubleshooting the Junos operating system and in monitoring device and protocol operations. This course uses Juniper Networks vMX Series Routers for the hands-on component, but the lab environment does not preclude the course from being applicable to other Juniper hardware platforms running the Junos OS. What will you learn Describe and configure OSPF area types and operations. Configure and monitor IS-IS. Describe basic BGP operation. Explain the causes for route instability. Describe how to troubleshoot routing policy. Explain the default behaviour of damping on links. Advanced Junos SP Routing course details Who will benefit: Network staff working with Junos at layer 3. Prerequisites: Junos Intermediate Routing Duration 5 days Advanced Junos SP Routing course contents OSPF OSPFv2 Review Link-State Advertisements Protocol Operations OSPF Authentication Lab: OSPF Multi-Area Networks Chapter 3: OSPF Areas Review of OSPF Areas Stub Area Operation and Configuration NSSA Operation and Configuration Route Summarization Lab: OSPF Route Summarization OSPF Case Studies and Solutions Virtual Links OSPF Multiarea Adjacencies External Reachability Lab: Advanced OSPF Options and Routing Policy Troubleshooting OSPF Troubleshooting OSPF Lab: OSPF Troubleshooting IS-IS Overview of IS-IS IS-IS PDUs Neighbors and Adjacencies Configuring and Monitoring IS-IS Lab: IS-IS Configuration and Monitoring Advanced IS-IS Operations and Configuration Options IS-IS Operations IS-IS Configuration Options IS-IS Routing Policy Lab: Advanced IS-IS Configuration Options and Routing Policy Multilevel IS-IS Networks Level 1 and Level 2 Operations Multilevel Configuration Lab: Configuring a Multilevel IS-IS Network Troubleshooting IS-IS Troubleshooting IS-IS Lab: IS-IS Troubleshooting BGP Review of BGP BGP Operations BGP Path Selection Options Configuration Options Lab: BGP and BGP Attributes BGP Attributes and Policy - Part1 BGP Policy Next Hop Origin and MED AS Path Lab: BGP Attributes - Next Hop, Origin, MED, and AS Path Attributes and Policy - Part2 Local Preference Communities Lab: BGP Attributes - Local Preference and Communities Route Reflection and Confederations Route Reflection Operation Configuration and Routing Knowledge BGP Confederations Lab: Scaling BGP BGP Route Damping Route Flap and Damping Overview Route Damping Parameters Configuring and Monitoring Route Damping Lab: BGP Route Damping Troubleshooting BGP Troubleshooting BGP Lab: BGP Troubleshooting Troubleshooting Policy Troubleshooting Policy Lab: Policy Troubleshooting

MEF Carrier Ethernet training course description The course progresses from a overview of the Carrier Ethernet service and how it works onto looking at the concepts in depth. Service attributes and management follow with the course finishing with studies of practical Carrier Ethernet. What will you learn Discuss and understand key Carrier Ethernet Concepts. Understand tasks related to designing, deploying and maintaining a Carrier Ethernet network. Offer effective solutions to implementing a Carrier Ethernet enterprise network given available customer resources and requirements. Carry out informed discussions using industry Carrier Ethernet 'vocabulary. Pass the MEF CECP 2.0 professional accreditation exam. MEF Carrier Ethernet training course details Who will benefit: Anyone working with Carrier Ethernet Prerequisites: The course attendees need to be conversant with data networks, as well as Ethernet and IP technologies. Duration 5 days MEF Carrier Ethernet training course contents Section One: Introduction to Carrier Ethernet Introduction to Carrier Ethernet: What is Carrier Ethernet? Evolution, advantages, The MEF, MEF specifications; UNI, EVC, OVC, EPL/EVPL, EP-LAN/ EVP-LAN, EP-Tree/EVP-Tree, etc, overview. How Carrier Ethernet Works: Service Frame Handling. Carrier Ethernet at Customer Premises, metro and core. Carrier Ethernet Workings, UNI attributes, Service Attributes (EVC and EVC per UNI attributes), Bandwidth Profiles, service multiplexing, L2 protocol processing; Carrier Ethernet equipment, CPE, aggregation and homing nodes, core equipment; management systems. The Setting Up of a Carrier Ethernet Service: Step 1: Choose service type, EPL/EVPL, EP-LAN/EVP-LAN, EPTree/EVP-Tree, EVLine...; Step 2: CPE tasks, UNI-C tasks (UNI attributes, service attributes (EVC and EVC per UNI) and bandwidth profiles), UNI-N tasks (L2 protocol handling). Step 3: Non-CPE tasks, Access, metro and core connections set up. Section Two: Carrier Ethernet Concepts in depth Carrier Ethernet Definitions in Depth: UNI, UNI I & II, UNI-N and UNI-C, etc.; NNI/ENNI; EVC; OVC, OVC type (P2P, M2M, Rooted MP), OVC end point (root, leaf, trunk), OVC end point map, OVC end point bundling; Service types in detail, EPL/EVPL, EP-LAN/EVP-LAN, EP-Tree/EVP-Tree, EVLine, Access EPL, Access EVPL . Carrier Ethernet Service Frame Handling: Unicast, multicast and broadcast frame delivery, Tagged, untagged and priority; Tagging, C and S-Tags, 802.3, 802.1d, 802.1q, 802.1ad, 802.1ah evolution, VLAN ID translation/preservation. CoS preservation. Other Key Carrier Ethernet Concepts: MTU, MTU at UNI, MTU at ENNI; Physical Layer Attributes, FE, GbE and 10GbE, Service Multiplexing and Bundling Concept and detail, rules and implications; Hairpin Switching Managing Bandwidth in a Carrier Ethernet Network: Token Bucket Algorithm, EIR, CIR, CBS, EBS, Coupling Flag; Frame Colors, recoloring, Color Awareness attribute, Color Forwarding; Bandwidth Profiles, rules and concepts. MEF CoS identifiers, DEI bit (in S-Tag), PCP bit (in C-Tag or S-Tag), or DSCP (in IP header), Multiflow bandwidth concepts; CoS Label/Color Identification. Section Three: Carrier Ethernet Service Attributes Overview: Carrier Ethernet 2.0; Blueprint C Service Attributes: Per UNI, Physical interfaces, Frame format, Ingress/egress Bandwidth Profiles, CEVLAN ID/EVC Map, UNI protection. EVC per UNI, Ingress/egress Bandwidth Profiles, etc.; Per EVC, CEVLAN ID Preservation, CoS ID Preservation, Relationship between SLA and SLP, Class of Service, etc. OVC, ENNI, OVC End Point per UNI and OVC End Point per ENNI, Ingress/egress bandwidth profiles, etc. Section Four: Managing Carrier Ethernet Networks Overview: MEF Service Lifecycle.Carrier Ethernet maintenance: Port, Link & NE failure, Service Protection Technologies, Fault Identification and Recovery, LAG, Active/Standby EVC, Single EVC with transport protection, G.8031, G.8032, MPLS FRR. SOAMs: Connectivity fault management, connectivity Monitoring, Loopback, Linktrace; Performance Management, Frame Delay, Inter Frame Delay Variation, Availability, Frame Loss Ratio, Resiliency, HLI, DMM, DMR, SLM, SLR; Key Concepts, Single vs dual ended, ordered UNI pair calculations. LOAMs: Link discovery, link monitoring, etc. Terminology and Concepts: MEG levels, MIPs. Section Five: Practical Carrier Ethernet Carrier Ethernet Transport Technologies:Layer 1: SDH. Layer 2: Bridging, provider bridging, PBB, PBBTE. Layer 2.5: MPLS VPWS, MPLS VPLS, MPLS-TP. Carrier Ethernet Access Technologies: fiber, SDH, active fiber, PON, GPON, 10G PON, OTN, WDM; copper, PDH, G-SDSL, 10Pass-TS, HFC; packet radio. Optimising mobile backhaul with Carrier Ethernet Key challenges solutions: Market pressure, LTE evolution, elements and architecture (RAN BS, NC, GWIF.), synchronization, bandwidth management. Circuit Emulation over Ethernet: Purpose, needs and applications. Synchronization: Phased, ToD, External Reference source, SynchE ,NTP, IEEE-1588 v2/ PTP, ACR; MEF Service Definitions for emulated circuits. Applying what you know: Practical examples and scenarios, Carrier Ethernet solutions; Practice Scenarios, Given a scenario, determine appropriate Ethernet services