124 Courses in Cardiff delivered Live Online

Data Visualization Courses London. In this Power BI Course, you will learn how to translate data trends, summaries, statistics and insights from your data into powerful and inspirational visualizations This course is ideal for managers and data analysts who need to make business decisions based on data.

This qualification consists of 2 mandatory components. Learners must complete both the Non-Calculator and Calculator written examinations. The assessments will assess a learner’s representing, analysing, and interpreting skills using numbers, geometry, and statistics in realistic contexts. To achieve an equivalent to GCSE grade C or 4. The qualification is awarded by Highfield OFQUAL-regulated and nationally recognised. Learn about the Functional Skills Qualification in Mathematics at Level 2 Our rolling 12-week course, via live webinar with a dedicated tutor, is designed to discover your weakness and build on those, to enable you to achieve success in Maths to allow you to progress your career in the direction you want. Every Wednesday 4pm – 6pm with full resources and practice papers – you will succeed. As part of one of our apprenticeship courses – This course could be government funded – so ask for more information. Course Dates Every Wednesday 4pm – 6pm 12 week rolling course Costs £350.00 per person (inc. VAT) Any additional resits of exams are charged at £30 each.

CWAP training course description This WiFi analysis course consists of hands-on learning using the latest enterprise wireless LAN analysis and troubleshooting tools. The course takes an in-depth look at the functionality of WLANs, intended operation of the 802.11 protocol and Wi-Fi Alliance specifications, WLAN frame formatting and structure, troubleshooting methodology, and protocol analysis. It also includes extensive training in modern spectrum analysis with a focus on advanced RF behaviour analysis, data collection methods, interpreting spectrum plots and charts, and understanding advanced features of WLAN spectrum analysers. What will you learn Analyse WiFi frames using Wireshark. Explain 802.11 protocol operation. Troubleshoot WiFi networks using Wireshark. Troubleshoot WiFi networks using spectrum analysers. CWAP training course details Who will benefit: Technical Network Staff Anyone looking to become a CWAP Prerequisites: Certified Wireless Network Administrator Duration 4 days CWAP training course contents Principles of WLAN Communication 802.11 Working Group, OSI reference model and the 802.11 PHY and MAC, Communication sublayers and data units, WLAN architecture components, Organization of station forwarding Addressing and internetworking operation, Modern WLAN product architectures. Physical (PHY) and MAC Layer Formats and Technologies Physical layer functions, Preamble function and format, Header purpose and structure, Analysis of PHY problems, Physical PPDU formats, 802.11b, 802.11a, 802.11g, 802.11n, MAC frame components, MAC encapsulation, Fields and subfields of the MAC header, Frame Control, Frame types and subtypes and their uses, Addressing, Frame body, Data frame format, Control frame format, Management frame format, Information elements and fields. Beaconing and synchronization Scanning, Client state machine, 802.11 contention, QoS, Admission control, Band steering and airtime fairness mechanisms Fragmentation, Acknowledgments and Block acknowledgments, Protection mechanisms and backward compatibility, Power management, Dynamic Frequency Selection (DFS) and Transmit Power Control (TPC), Security components, methods, and exchanges, Roaming procedures exchanges, Future protocol enhancements. 802.11n Transmit beamforming, Spatial multiplexing, Maximal Ratio Combining (MRC), Space-Time Block Coding, 40 MHz channels, Frame aggregation, HT-OFDM format, Modulation and Coding Schemes (MCS), HT frame formatting and more. Protocol Analysis Tools and Methodology Troubleshooting methodology, Protocol analyser types, Analysis NIC/adapter selection and constraints, Interpreting results based on location, Analyzer settings and features, Filtering and channel scanning, Interpreting decodes, Using advanced analysis features, Assessing WLAN health and behaviour factors, Evaluating network statistics, Troubleshooting common problems, Wired analysis to support wireless network issues. Spectrum Analysis Tools and Methodology Radio frequency behaviour review, Visualizing RF domains using spectrum measurement tools, Spectrum analyser types and operation, Analyser specifications and characteristics, Understanding spectrum data presentation, Interpreting plots and charts, Common WLAN spectrum analyser features, Identifying transmit patterns, Device classification and network impact, Recognizing transmit signatures. Hands on lab exercises Wireshark Setup, Use, and In-Depth Analysis Wireshark is fundamental to troubleshooting. Labs include: - Capabilities, configuration, and data display - Opening, collecting, saving, and modifying capture files. - Filtering traffic, and using colouring rules as analysis aides. - Live captures based on a set of desired collection criteria. - Identify and isolate network problems. - Conversation analysis. - Remote packet capture with an AP. Understanding Frame Components Familiarity with the frame structure and contents is essential in real -world troubleshooting efforts. Labs include: - Understanding the MAC header - Comparing the three major frame types and their subtypes - Analysing frame formats of individual frame types - Analysing 802.11n frame components - Additional information is reported by protocol analysers - Information not visible in protocol analysers Frame Exchanges Understanding frame exchange rules and behaviors is critical to identifying expected and unexpected. It is also necessary to understand what is normal so that aberrations can be properly troubleshot. Labs include: - Connectivity exchanges and sequences - Legacy and modern security exchanges - ERP and HT protection mechanisms - Power save behaviour - Acknowledgments, block acknowledgments, and supporting action frames - Dynamic rate switching - Band steering Troubleshooting Common Problems This lab exposes students to hands-on troubleshooting skills by setting up common problems in WLANs and allowing students to attempt to solve them. - Trouleshooting connectivity exchanges - Troubleshooting 802.1X and EAP exchanges - Troubleshooting roaming Spectrum Analyzer Setup, Use, and In-Depth Analysis Specifically, it will explore the plots and charts used to display spectrum data and how to interpret this data to define a transmitter's impact on the network. The following are covered: - Installing the analyser and using display and navigation - The 'RF perspective' provided by each plot and chart - Using built-in features and automated device identification - Characterizing the behaviours of an interference source - Assessing the impact of an interference source - Determining the impact of transmitter proximity on interference. - Identifying signatures of common transmitters - Remote spectrum analysis with an AP

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A 10 week SATs Success course for students in year 6. Tutoring in English and Tutoring in Maths in a small group year 6 tutor session.

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)

Duration 5 Days 30 CPD hours This course is intended for This intermediate-level course requires students have incoming experience working with Oracle Database 18 or higher. Overview Working in a hands-on learning environment led by our expert facilitator, you'll explore: The Oracle Database Architecture Query Optimizer Tuning Container Databases and Pluggable Databases Oracle 19c Tuning features Evaluating Execution Plans Oracle Tuning Tools Using Automatic Workload Repository Join Types AWR Using Baselines Additional AWR performance tools Optimizer Statistics Monitoring a Service Bind Variables and database parameters Oracle's Real Application Testing (RAT) SQL Tuning Advisor Automatic Sql Tuning Sql Plan Management Shared Pool Tuning Tuning the database buffer cache Tuning the PGA (Program Global Area) Automatic Memory Management (AMM) Tuning Segment Space Utilization (ASSM) Automatic Storage Management Oracle 19C Database Tuning is an intermediate level course for Oracle database experienced attendees that explores core tuning skills such as Database parameters, SQL Tuning Advisor, SQL Access Advisor, Adaptive SQL plans and more. Overview Oracle Database Architecture Instance Definition Define SGA Define Background Processes Datafile Definition Query Optimizer SQL Parsing Optimizing Terms Optimizing Methods Query Plan Generation Query Plan Control Tuning Container Databases and Pluggable Databases Pluggable tuning parameters Define Container tuning structure Using PDB$SEED Create a new PDB Plug and unplug a PDB Oracle 12c Tuning features Identifying and Using Oracle's Heat Map 12c Compression Levels and Types Evaluating Execution Plans Defining SQL execution plans Automatic Workload Repository Reading execution plans Oracle Tuning Tools Monitoring tools overview Enterprise Manager Dynamic Performance Views Automatic Workload Repository Automatic Database Diagnostic Monitor Sql Tuning Advisor SQL Access Advisor Sql Access Advisor DB operation Tuning DB operation Active Reporting Using Automatic Workload Repository Defining AWR AWR Settings Creating AWR Baselines Metrics, Alerts, and Thresholds Defining Metrics Setting Alerts Setting Corrective Actions User Defined Metrics Metric Dynamic Views Join Types Nested Loops Join Sort Merge join Hash Join and Cartesian Join Equijoins and Nonequijoins Outer Joins Semijoins AWR Using Baselines Creating AWR baselines Creating AWR Repeating baselines Moving Window Baseline Additional AWR performance tools Automatic Maintenance Tasks Segment Advisor Statistics Gathering Automatic Tuning Optimizer Automatic Database Diagnostic Monitor Active Session History (ASH) Optimizer Statistics Optimizer Statistics Overview Table and Index Statistics Statistic Preferences Statistics Gathering e) Locking Statistics, Export/Import Statistics Pending and published statistics Optimizer Hints Optimizer Paths Cost Base Optimization Monitoring a Service Overview of what is an Oracle Service Creating an Oracle Service for Single instance and RAC Monitoring a Service Resource Management and a Service Enterprise Manager and a Service Bind Variables and database parameters Bind variable definition Cursor_sharing parameter Adaptive Cursor Sharing Oracle's Real Application Testing (RAT) Sql Performance Analyzer overview Sql Performance Analyzer Options Database Parameter changes Database version changes Creating SQL Tuning Sets Database Replay Overview Database Replay Configuration Database Replay Options SQL Tuning Advisor SQL Tuning Advisor: Overview SQL Tuning Advisor Limited Mode Sql Tuning Advisor Comprehensive mode Sql Tuning Profiles SQL Access Advisor SQL Access Advisor: Overview Sql Access Advisor options SQL Access Advisor and Sql Tuning Sets Sql Access Advisor and AWR Results and Implementation Automatic Sql Tuning Automatic Sql Tuning Maintenance Task Automatic Tuning Optimization implementation(ATO) Automatic Tuning Optimization Results Enable/Disable Automatic Tuning Optimization Sql Plan Management Sql plan Management and baseline overview Enable sql plan management Loading Sql Plan baselines into the SGA Adaptive plan management Shared Pool Tuning Shared pool architecture Shared pool parameters Library Cache Dictionary cache Large pool considerations and contents Tuning the database buffer cache Database buffer cache overview Database buffer cache parameters Oracle and Dirty reads and writes Automatic Shared Memory Management (ASMM) Buffer Cache goals and responsibility Buffer Cache pools Tuning the PGA (Program Global Area) PGA Overview PGA Database Parameters Temporary Segments Temporary Tablespace Sizing the PGA Automatic Memory Management (AMM) Oracle's Automatic Memory Management Overview Database Auto-tuned Parameters Database Non Auto-tuned Parameters Automatic Memory Management Hints and Sizing suggestions AMM versus ASMM Tuning Segment Space Utilization (ASSM) Overview of Automatic Segment Space Management Defining the DB_BLOCK_SIZE Defining DB_nk_CACHE_SIZE parameter The DB_BLOCK_SIZE Parameter Overview of table compression, block chaining, and block migration Automatic Storage Management Overview of ASM Definition of Grid Infrastructure ASM Instance ASM Diskgroups ASM Diskgroup parameters and templates ASMCMD

About this Virtual Instructor Led Training (VILT)  A decision to drill an exploration well with the objective to find a new oil or gas field must be based on sound assessment of the prospect risk and of the volumes. What is the chance that a well will find hydrocarbons, and how much could it be? Risk and volume assessments form the basis for decisions to drill a well or not, and as such form the link between subsurface evaluation and the business aspects of the petroleum industry. This Virtual Instructor Led Training (VILT) course explains how risks and volumes can be assessed in a realistic manner, based on a sound understanding of the geological details of the prospect as well as its regional geological setting and current play understanding. Participants of this VILT course will receive a softcopy of Risk and Volume Assessment Handbook which explains the concepts that are associated with probabilistic Risk & Volume (R & V) Assessment and contains many practical recommendations on how to translate geological understanding into meaningful inputs for probabilistic R &V assessments. The book is fully compatible with any probabilistic R & V tool in the industry. Training Objectives By the end of this VILT course, participants will be able to understand: The fundamentals of risk and volumes assessment; translating geological understanding into reasonable numbers and ranges. The difference between risk and uncertainty. Fundamentals of statistics; including explanation of distribution curves, understanding of expectation curves, do's and don'ts for adding risked volumes, and Bayes theorem. Uncertainty of trap, reservoir, seal and charge, illustrated by examples. Guidelines and exercises for estimating risks realistically and consistently. Calculating volume ranges for prospects and for portfolios of prospects; how to add prospect volumes for a correct representation of prospect portfolios. Incorporation of geophysical evidence (DHIs) in a realistic risk assessment. Target Audience This VILT course has been designed in the first place for geoscientists working in exploration, for prospect portfolio analysts and for their direct supervisors. It will also benefit staff from disciplines working closely with exploration staff, such as reservoir engineers, petrophysicists and geophysicists. Course Level Intermediate Training Methods Learning, methods and tools The VILT course will be delivered online in 5 half-day sessions comprising 4 hours per day, with 2 breaks of 10 minutes per day. It is the intention to have at least 2 smaller exercises per day. Time will be reserved for recapitulation, questions and discussions. VILT will be conducted either via Zoom or Microsoft Teams. Presenting materials can easily be done on this platform. When participants need to ask a question, they can raise their hand, write notes or interrupt the Instructor by using their microphone. The presenter can switch to a screen where he/she can see all participants (also when each participant is sitting in another location e.g. at home). There is also a whiteboard functionality that can be used as one would use a flip chart. Exercises will be done on an online platform which provides each participant with a private work area that can be accessed by the Instructor to discuss the exercise in a similar manner as in a classroom course. Each topic is introduced by a lecture, and learning is re-enforced by practical exercises and discussions. Handout material in electronic format will be provided. Trainer Dr. Jan de Jager has a PhD in Geology from the University of Utrecht. He joined Shell in 1979 as an exploration geologist, and worked in several locations around the world such as Netherlands, Gabon, USA, Australia, Argentina, and Malaysia in technical and management positions. During the last 10 years of his career, he was responsible for the quality assurance of Shell's exploration prospects in many parts of the world and for upgrading and replenishing Shell's global exploration portfolio. During this period, he had also developed extensive expertise in Prospect Risk and Volume assessments for which he ran successful internal training programmes. Following his retirement from Shell in 2010, Dr Jan de Jager took on a position as part-time professor at the University of Amsterdam and also serves as a consultant exploration advisor for various E&P companies. POST TRAINING COACHING SUPPORT (OPTIONAL) To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster. Request for further information about post training coaching support and fees applicable for this. Accreditions And Affliations

Lean Six Sigma Black Belt Certification Program: Virtual 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)

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