2652 Courses in London

Application delivery training course description A concise hands on course covering section 1 of the F5 networks AD fundamentals exam. The course focuses on the technology and not any one manufacturers product. This will enable delegates to work with devices from any manufacturer. Practical hands on with Cisco and Microsoft systems follow the major sessions to reinforce the theory. What will you learn Explain, compare and contrast the OSI layers. Explain protocols and technologies specific to the data link layer. Explain protocols and apply technologies specific to the network layer. Explain the features and functionality of protocols and technologies specific to the Transport layer. Explain the features and functionality of protocols and technologies specific to the Application layer Application delivery training course details Who will benefit: Anyone taking the F5 networks AD fundamentals exam. Technical staff working in Application delivery. Prerequisites: None. Duration 3 days Application delivery training course contents What is TCP/IP? Protocols, services. The Internet, RFCs, The OSI 7 layer model. Layer 1 cables. Ping and addressing Host configuration of IP addresses, subnet masks, default gateways, ipconfig, ping. Hands on Configuring TCP/IP, ping. Ethernet and the data link layer 802.3, evolution, choosing cables, topologies, CSMA/CD, hubs, NICs, MAC addresses. Hands on Analysing MAC addresses. IP and Ethernet Relationship. Hands on ARP. What is a switch? Switches connect multiple devices, switches versus hubs, simultaneous conversations, switches work at layer 2, the forwarding database, how the forwarding database is built, broadcast and collision domains. Hands on Difference between hubs and switches. Link aggregation Loops, broadcast storms, STP, Architectures, modes, link aggregation, load sharing, resilience. Hands on fail over times. VLANs Virtual versus physical LANs, Why have VLANs? Broadcast domains. Hands on VLANs effect on traffic. IP IP datagram format, ICMP datagram format. Hands on Analysing IP and ICMP packets. IP addressing Format of addresses, registering, dotted decimal notation, choosing addresses, DHCP. Hands on impact of addressing errors. Routing What is a router? Reason for routing, network addressing, default gateways, how routing works, routing and addresses, routing tables, traceroute. Hands on Using a routed network. Routing protocols IGPs, EGPs, RIP & OSPF. Hands on Configuring routers for RIP and OSPF. Subnetting When to subnet, subnet masks, working with subnetting, CIDR notation. Hands on Changing the routed network to use subnetting. The transport layer UDP, Ports, TCP, acknowledgements, sliding windows. Hands on Analysing packets. Applications Clients, servers, web, Email SMTP, resource sharing, IM, VoIP, Video over IP, terminal emulation, FTP. Hands on FTP, SIP. Web pages URLs, DNS, names to IP addresses. HTTP, versions and status codes. Keepalives, cookies. Hands on Analysing HTTP headers.

About this training course Artificial lift systems are an important part of production operations for the entire lifecycle of an asset. Often, oil and gas wells require artificial lift for most of the life cycle. This 5-day training course offers a thorough treatment of artificial lift techniques including design and operation for production optimization. With the increasing need to optimize dynamic production in highly constrained cost environments, opportunities and issues related to real-time measurements and optimization techniques needs to be discussed and understood. Artificial lift selection and life cycle analysis are covered. These concepts are discussed and reinforced using case studies, quizzing tools, and exercises with software. Participants solve examples and class problems throughout the course. Animations and videos reinforce the concepts under discussion. Understanding of these important production concepts is a must have to exploit the existing assets profitably. Unique Features: Hands-on usage of SNAP Software to solve gas-lift exercises Discussion on digital oil field Machine learning applications in gas-lift optimization Training Objectives After the completion of this training course, participants will be able to: Understand the basics and advanced concepts of each form of artificial lift systems including application envelope, relative strengths, and weaknesses Easily recognize the different components from downhole to the surface and their basic structural and operational features Design and analyze different components using appropriate software tools Understand challenges facing artificial lift applications and the mitigation of these challenges during selection, design, and operation Learn about the role of digital oilfield tools and techniques and their applications in artificial lift and production optimization Learn about use cases of Machine learning and artificial intelligence in the artificial lift Target Audience This training course is suitable and will greatly benefit the following specific groups: Production, reservoir, completion, drilling and facilities engineers, analysts, and operators Anyone interested in learning about selection, design, analysis and optimum operation of artificial lift and related production systems will benefit from this course. Course Level Intermediate Advanced Training Methods The training instructor relies on a highly interactive training method to enhance the learning process. This method ensures that all participants gain a complete understanding of all the topics covered. The training environment is highly stimulating, challenging, and effective because the participants will learn by case studies which will allow them to apply the material taught in their own organization. Course Duration: 5 days in total (35 hours). Training Schedule 0830 - Registration 0900 - Start of training 1030 - Morning Break 1045 - Training recommences 1230 - Lunch Break 1330 - Training recommences 1515 - Evening break 1530 - Training recommences 1700 - End of Training The maximum number of participants allowed for this training course is 20. This course is also available through our Virtual Instructor Led Training (VILT) format. Prerequisites: Understanding of petroleum production concepts. Each participant needs a laptop/PC for solving class examples using software to be provided during class. Laptop/PC needs to have a current Windows operating system and at least 500 MB free disk space. Participants should have administrator rights to install software. Trainer Your expert course leader has over 35 years' work-experience in multiphase flow, artificial lift, real-time production optimization and software development/management. His current work is focused on a variety of use cases like failure prediction, virtual flow rate determination, wellhead integrity surveillance, corrosion, equipment maintenance, DTS/DAS interpretation. He has worked for national oil companies, majors, independents, and service providers globally. He has multiple patents and has delivered a multitude of industry presentations. Twice selected as an SPE distinguished lecturer, he also volunteers on SPE committees. He holds a Bachelor's and Master's in chemical engineering from the Gujarat University and IIT-Kanpur, India; and a Ph.D. in Petroleum Engineering from the University of Tulsa, USA. Highlighted Work Experience: At Weatherford, consulted with clients as well as directed teams on digital oilfield solutions including LOWIS - a solution that was underneath the production operations of Chevron and Occidental Petroleum across the globe. Worked with and consulted on equipment's like field controllers, VSDs, downhole permanent gauges, multiphase flow meters, fibre optics-based measurements. Shepherded an enterprise-class solution that is being deployed at a major oil and gas producer for production management including artificial lift optimization using real time data and deep-learning data analytics. Developed a workshop on digital oilfield approaches for production engineers. Patents: Principal inventor: 'Smarter Slug Flow Conditioning and Control' Co-inventor: 'Technique for Production Enhancement with Downhole Monitoring of Artificially Lifted Wells' Co-inventor: 'Wellbore real-time monitoring and analysis of fracture contribution' Worldwide Experience in Training / Seminar / Workshop Deliveries: Besides delivering several SPE webinars, ALRDC and SPE trainings globally, he has taught artificial lift at Texas Tech, Missouri S&T, Louisiana State, U of Southern California, and U of Houston. He has conducted seminars, bespoke trainings / workshops globally for practicing professionals: Companies: Basra Oil Company, ConocoPhillips, Chevron, EcoPetrol, Equinor, KOC, ONGC, LukOil, PDO, PDVSA, PEMEX, Petronas, Repsol, , Saudi Aramco, Shell, Sonatrech, QP, Tatneft, YPF, and others. Countries: USA, Algeria, Argentina, Bahrain, Brazil, Canada, China, Croatia, Congo, Ghana, India, Indonesia, Iraq, Kazakhstan, Kenya, Kuwait, Libya, Malaysia, Oman, Mexico, Norway, Qatar, Romania, Russia, Serbia, Saudi Arabia, S Korea, Tanzania, Thailand, Tunisia, Turkmenistan, UAE, Ukraine, Uzbekistan, Venezuela. Virtual training provided for PetroEdge, ALRDC, School of Mines, Repsol, UEP-Pakistan, and others since pandemic. 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 post training support and fees applicable Accreditions And Affliations

Zeroconf and Bonjour training course description A hands on training course focusing on Microsoft and Apple implementations of Zeroconf. The course covers all three main areas: Interface configuration, name resolution and service discovery. Hands on with Apple Bonjour and Microsoft UPnP compliment all the major theory sessions. What will you learn Explain how mDNS and LLMNR work. Explain how DNS-SD and SSDP work. Recognise the role of service discovery gateways. Zeroconf and Bonjour training course details Who will benefit: Technical staff working with Zeroconf. Developers using Zeroconf. Prerequisites: TCP/IP Foundation for engineers Duration 2 day Zeroconf and Bonjour training course contents What is Zeroconf? Zeroconf, architecture, Microsoft UPnP, Apple, Bonjour, devices, components. Home networks, enterprise networks, BYOD. Plug and play without Zeroconf DHCP, DNS, A, PTR, SRV records, DDNS. Hands on DHCP configuration. Address selection IPv4 link local addresses, IPv6 link local addresses. Hands: Addresses without DHCP. Name resolution mDNS, finding names, announcing names, .local DNS namespace, LLMNR. Hands on Names without DNS. Role of multicasting Multicast addresses, multicasts and switches, multicasts and routers. Hands on Multicasts, TTL. Service discovery DNS-SD, SRV and TXT lookups, SSDP, HTTP. Hands on Browsing for services Zeroconf in a routed environment Service Discovery gateways, configuration, service filters, DNS-LLQ, NAT-PMP. Miscellaneous Security, automatic multicast addresses, wireless auto configuration.

About this training course Business Impact: The main aim is to provide insight and understanding of data analytics and machine learning principles through applications. Field data is used to explain data-analysis workflows. Using easy to follow solution scripts, the participants will assess and extract value from the data sets. Hands-on solution approach will give them confidence to try out applicable techniques on data from their field assets. Data analysis means cleaning, inspecting, transforming, and modeling data with the goal of discovering new, useful information and supporting decision-making. In this hands-on 2-day training course, the participants learn some data analysis and data science techniques and workflows applied to petroleum production (specifically artificial lift) while reviewing code and practicing. The focus is on developing data-driven models while keeping our feet closer to the underlying oil and gas production principles. Unique Features: Eight business use cases covering their business impact, code walkthroughs for most all and solution approach. Industry data sets for participants to practice on and take home. No software or complicated Python frameworks required. Training Objectives After the completion of this training course, participants will be able to: Understand digital oil field transformation and its impact on business Examine machine learning methods Review workflows and code implementations After completing the course, participants will have a set of tools and some pathways to model and analyze their data in the cloud, find trends, and develop data-driven models Target Audience This training course is suitable and will greatly benefit the following specific groups: Artificial lift, production and facilities engineers and students to enhance their knowledge base, increase technology awareness, and improve the facility with different data analysis techniques applied on large data sets Course Level Intermediate Advanced Training Methods The course discusses several business use-cases that are amenable to data-driven workflows. For each use case, the instructor will show the solution using a data analysis technique with Python code deployed in the Google cloud. Trainees will solve a problem and tweak their solution. Course Duration: 2 days in total (14 hours). Training Schedule 0830 - Registration 0900 - Start of training 1030 - Morning Break 1045 - Training recommences 1230 - Lunch Break 1330 - Training recommences 1515 - Evening break 1530 - Training recommences 1700 - End of Training The maximum number of participants allowed for this training course is 20. This course is also available through our Virtual Instructor Led Training (VILT) format. Prerequisites: Understanding of petroleum production concepts Knowledge of Python is not a must but preferred to get the full benefit. The training will use the Google Collaboratory environment available in Google-Cloud for hands-on exercises Trainees will need to bring a computer with a Google Chrome browser and a Google email account (available for free) Trainer Your expert course leader has over 35 years' work-experience in multiphase flow, artificial lift, real-time production optimization and software development/management. His current work is focused on a variety of use cases like failure prediction, virtual flow rate determination, wellhead integrity surveillance, corrosion, equipment maintenance, DTS/DAS interpretation. He has worked for national oil companies, majors, independents, and service providers globally. He has multiple patents and has delivered a multitude of industry presentations. Twice selected as an SPE distinguished lecturer, he also volunteers on SPE committees. He holds a Bachelor's and Master's in chemical engineering from the Gujarat University and IIT-Kanpur, India; and a Ph.D. in Petroleum Engineering from the University of Tulsa, USA. Highlighted Work Experience: At Weatherford, consulted with clients as well as directed teams on digital oilfield solutions including LOWIS - a solution that was underneath the production operations of Chevron and Occidental Petroleum across the globe. Worked with and consulted on equipment's like field controllers, VSDs, downhole permanent gauges, multiphase flow meters, fibre optics-based measurements. Shepherded an enterprise-class solution that is being deployed at a major oil and gas producer for production management including artificial lift optimization using real time data and deep-learning data analytics. Developed a workshop on digital oilfield approaches for production engineers. Patents: Principal inventor: 'Smarter Slug Flow Conditioning and Control' Co-inventor: 'Technique for Production Enhancement with Downhole Monitoring of Artificially Lifted Wells' Co-inventor: 'Wellbore real-time monitoring and analysis of fracture contribution' Worldwide Experience in Training / Seminar / Workshop Deliveries: Besides delivering several SPE webinars, ALRDC and SPE trainings globally, he has taught artificial lift at Texas Tech, Missouri S&T, Louisiana State, U of Southern California, and U of Houston. He has conducted seminars, bespoke trainings / workshops globally for practicing professionals: Companies: Basra Oil Company, ConocoPhillips, Chevron, EcoPetrol, Equinor, KOC, ONGC, LukOil, PDO, PDVSA, PEMEX, Petronas, Repsol, , Saudi Aramco, Shell, Sonatrech, QP, Tatneft, YPF, and others. Countries: USA, Algeria, Argentina, Bahrain, Brazil, Canada, China, Croatia, Congo, Ghana, India, Indonesia, Iraq, Kazakhstan, Kenya, Kuwait, Libya, Malaysia, Oman, Mexico, Norway, Qatar, Romania, Russia, Serbia, Saudi Arabia, S Korea, Tanzania, Thailand, Tunisia, Turkmenistan, UAE, Ukraine, Uzbekistan, Venezuela. Virtual training provided for PetroEdge, ALRDC, School of Mines, Repsol, UEP-Pakistan, and others since pandemic. 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 post training support and fees applicable Accreditions And Affliations

PMI-PBA® Exam Prep The course provides targeted exam preparation support for PMI®'s Professional in Business Analysis exam candidates, including a content review of The PMI Guide to Business Analysis, a review of the PMI-PBA® reference books, and an exam preparation tutorial. You will be given a Study Guide that you can re-use to assess your knowledge gaps as part of your Personal Action Plan. Your score on this for each Knowledge Area can be compared to your results on the quiz at the end of each course module to guide your study efforts. What you will Learn Upon completion, participants will be able to: Demonstrate familiarity with the structure, content and framework of The PMI Guide to Business Analysis Explain the six Knowledge Areas of The PMI Guide to Business Analysis, as well as, their inter-relationships with each other and the six Process Groups Differentiate among the five business analysis domains in the project life cycle Create a personal action plan to study and prepare for the PMI-PBA® Exam Getting Started PMI-PBA Examination Certification Process The Credential Examination Foundation Concepts for PMI-PBA® Prep Business analysis terminology and definitions Business analysis project, program, and portfolio management Product and project life cycles Skills and qualities of a business analyst Introduction to Business Analysis in Projects Business analysis overview How organizations implement business analysis Business analyst and project manager relationships Requirements definitions and types Practice quiz On-Demand Segment A: Define the Business Problem (Pre-work for Needs Assessment) Needs Assessment Review Needs Assessment knowledge area Identify problem or opportunity Assess current and future state Determine options and provide recommendations Facilitate product roadmap development Assemble business case Practice quiz Stakeholder Engagement Review Stakeholder Engagement knowledge area Identify Stakeholders and conduct analysis Determine Stakeholder engagement and communication approach Conduct business analysis planning Practice quiz On-Demand Segment B: The Elicitation Plan (Pre-work for Elicitation) Elicitation Review Elicitation knowledge area Determine Elicitation approach Preparing for Elicitation Conducting Elicitation Confirming Elicitation results Practice quiz On-Demand Segment C: Overview of Requirements Analysis (Pre-work for Analysis) Analysis Review Analysis knowledge area Determine Analysis approach Create and analyze models Define requirements and acceptance criteria Verify, validate, and prioritize requirements Identify and analyze product risks Assess product design options Practice quiz Traceability and Monitoring Review Traceability and Monitoring knowledge area Determine Traceability and Monitoring approach Establish relationships and dependencies Select and approve requirements Make changes to requirements and other product information Practice quiz Solution Evaluation Review Solution Evaluation knowledge area Evaluate solution performance Determine solution evaluation approach Evaluate acceptance results and address defects Obtain solution acceptance for release Practice quiz Exam Application and Preparation Process Applying for the Exam Studying for the Exam Sitting for the Exam Reviewing your Knowledge Gap Practice Exam Study Guide - a reliable learning aid Summary and Next Steps Crystallizing the Business Analysis Domains Developing a Personal Action Plan for Exam Study

PMI-PBA® Exam Prep: In-House Training The course provides targeted exam preparation support for PMI®'s Professional in Business Analysis exam candidates, including a content review of The PMI Guide to Business Analysis, a review of the PMI-PBA® reference books, and an exam preparation tutorial. You will be given a Study Guide that you can re-use to assess your knowledge gaps as part of your Personal Action Plan. Your score on this for each Knowledge Area can be compared to your results on the quiz at the end of each course module to guide your study efforts. What you will Learn Upon completion, participants will be able to: Demonstrate familiarity with the structure, content and framework of The PMI Guide to Business Analysis Explain the six Knowledge Areas of The PMI Guide to Business Analysis, as well as, their inter-relationships with each other and the six Process Groups Differentiate among the five business analysis domains in the project life cycle Create a personal action plan to study and prepare for the PMI-PBA® Exam Getting Started PMI-PBA Examination Certification Process The Credential Examination Foundation Concepts for PMI-PBA® Prep Business analysis terminology and definitions Business analysis project, program, and portfolio management Product and project life cycles Skills and qualities of a business analyst Introduction to Business Analysis in Projects Business analysis overview How organizations implement business analysis Business analyst and project manager relationships Requirements definitions and types Practice quiz On-Demand Segment A: Define the Business Problem (Pre-work for Needs Assessment) Needs Assessment Review Needs Assessment knowledge area Identify problem or opportunity Assess current and future state Determine options and provide recommendations Facilitate product roadmap development Assemble business case Practice quiz Stakeholder Engagement Review Stakeholder Engagement knowledge area Identify Stakeholders and conduct analysis Determine Stakeholder engagement and communication approach Conduct business analysis planning Practice quiz On-Demand Segment B: The Elicitation Plan (Pre-work for Elicitation) Elicitation Review Elicitation knowledge area Determine Elicitation approach Preparing for Elicitation Conducting Elicitation Confirming Elicitation results Practice quiz On-Demand Segment C: Overview of Requirements Analysis (Pre-work for Analysis) Analysis Review Analysis knowledge area Determine Analysis approach Create and analyze models Define requirements and acceptance criteria Verify, validate, and prioritize requirements Identify and analyze product risks Assess product design options Practice quiz Traceability and Monitoring Review Traceability and Monitoring knowledge area Determine Traceability and Monitoring approach Establish relationships and dependencies Select and approve requirements Make changes to requirements and other product information Practice quiz Solution Evaluation Review Solution Evaluation knowledge area Evaluate solution performance Determine solution evaluation approach Evaluate acceptance results and address defects Obtain solution acceptance for release Practice quiz Exam Application and Preparation Process Applying for the Exam Studying for the Exam Sitting for the Exam Reviewing your Knowledge Gap Practice Exam Study Guide - a reliable learning aid Summary and Next Steps Crystallizing the Business Analysis Domains Developing a Personal Action Plan for Exam Study

Unconscious bias from a fresh new perspective for anyone who interacts with, or makes decisions about, people; whether you work with customers, supervise staff or work in collaboration, this session will enhance your insight and interactions.

Solution-Focused Coaching Model Grow Coaching Model 0SKAR Coaching Model CLEAR Coaching Model AOR Coaching Model FUEL Coaching Model WOOP Coaching Model COACHING PROCEDURE FOR COACHING FOR CEOS: Pre-session check-in and questionnaire and assessment Mindset Analysis and introspection testing Psychological analysis Follow up for feedback and well-being and progress check-up calls Accountability Coaching Anxiety Coaching Target-driven coaching helpful for individuals with procrastination issues or issues tackling challenging career goals Leadership Coaching and Self-belief Coaching Organizational objective coaching Bring awareness to self-talk and unconscious biases 24/7 ACCESS TO YOUR COACH Coach available on Whatsapp, Phone, Zoom, and Face to Face   CEO Coaching helps coach the world’s best CEOs, executives, entrepreneurs, and companies to increase revenue and grow their business. Our coaches have extensive real-world experience in overcoming the challenges, inherent in entrepreneurship and executive leadership. Consult with a CEO coach today to receive a customized business plan that will enable you to achieve extraordinary results. We work with you by understanding the business issues and strategic imperatives of the enterprise. We then use a combination of 360 feedback (including Board members) and formal assessment tools to ensure we have a clear picture of you as an individual leader and the environment in which you need to create success. We assess your team and work with you to understand where you’ve got the capability and where the team may be vulnerable. https://relationshipsmdd.com/product/coaching-for-ceos-package/

Overview This course is specially designed to give you intense knowledge and walk you through steps of proven approaches to Public Relations (PR) planning and management. The skills attained through this course can be very well measured and implemented within their work organisation thereby contributing towards the growth of their organisation also helping to build a good reputation and maintaining healthy relationships.  You will be shown how the fundamentals of PR are vital, and how significant they are to understanding organisational reputation and relationships. PR professionals are mostly considered as challenging positions and many times have to deal with difficult and even different situations. Therefore, attending this course will enable you to gain the skills needed to present practical and achievable plans.

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)