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We offer the most advanced “Certified Six Sigma Green Belt Course” as per the curriculum outline of The ASQ Body of Knowledge and accredited by top international Lean & Six Sigma accreditation bodies. Six Sigma Green Belt Deliverables: 22+ hours of Instructor-led interactive virtual classroom session on the weekend Access to 45+ hours of Module based Six Sigma lectures via LMS 100+ Toolkits and Project Templates for Analysis and Implementation Soft copy of Lean Six Sigma Green Belt Body of Knowledge Live Data-oriented project, with Scenario and Analysis Methodology 20+ Dummy Projects and Case studies for Lean Six Sigma Application Support via subject expert through telephonic discussion on the weekend Sample Questions and Examination Guide for Certification Preparation Pre and Post assignments for process groups and knowledge areas Project implementation support and Data visualization using MINITAB PRO CLSSGB certification examination anytime within the 90 days course duration Certification Validation Tool for third-party credentials validation PARTICULARS Duration (Hours) 1. Define Phase 22 2. Measure Phase 14 3. Analyse Phase 20 4. Improve Phase 7 5. Control Phase 7 Total Duration 70 (Hours) Introduction Become an expert in six sigma methodology by getting hands-on knowledge on DMAIC, Project Charter, Process Capability, FMEA, Sigma calculation, Test of Hypothesis, Control Charts, VSM, JIT using real case scenarios and real-life examples. Lean and DMAIC methodologies using live projects. The Six Sigma Certification is accredited by The Council for Six Sigma Certification. The certification also acknowledges the BOK outline of The American Society for Quality, USA. The course features world-class content with live projects and MINITAB PRO driven data analysis training with end to end support in project implementation by Master Black Belt Experts and Trainers. What is Six Sigma Certification? A person with Six Sigma certification has problem-solving abilities. Someone may gain Green Belt, Black Belt or Master Black Belt certification. The higher certification one attains, the more is the ability to solve complex organizational problems. Six Sigma certification is a process of individual’s knowledge validation using a classification system, generally referred to as "Belts" (Green Belt, Black Belt, Master Black Belt) This verification test individual commands over six sigma methodology and tools. The belt classification shows the position these certified individuals would occupy in an organizational structure and job roles. Six Sigma Green Belt training is especially for the future project leaders of Lean Six Sigma projects. We deliberately mix non-profit with profit participants. There will then be fun, useful discussions and knowledge exchanges during the training sessions. In addition, there are also many self-employed people who follow the LSS Green Belt training to increase their expertise as in a trimmer. What do you do to get the Six Sigma Green Belt certificate? Our Six Sigma Green Belt training consists of a number of components: Training: in an intensive training program you learn the background of Lean and Six Sigma and we put what we have learned into practice with different simulations. Extra: With our Body of Knowledge and whitepapers you place what you have learned in a theoretical framework. The program also contains various homework assignments, in which we focus, among other things, on the use of MINITAB PRO. Follow-up: During the training, you will receive an access code to an e-learning module. You can pass the substance again in an interactive way. Exam: On the last training day you will make the CLSSGB Green Belt exam. If you succeed, you will immediately receive the official Certified Lean Six Sigma Green Belt certification. Global Recognition of Your Certification: Agenda Overview of Six Sigma and the organizationSix Sigma and organizational goalsValue of six sigmaOrganizational goals and six sigma projectsOrganizational drivers and metricsLean principles in the organizationLean conceptsValue-streaming mappingDesign for six sigma (DFSS) methodologiesRoadmaps for DFSSBasic failure mode and effects analysis (FMEA)Design FMEA and process FMEA Define PhaseProject identificationProject SelectionProcess elementsBenchmarkingProcess inputs and outputsOwners and stakeholders Voice of the customer (VOC) Customer identificationCustomer dataCustomer requirements Project Management Basics Project charterProject scopeProject metricsProject planning toolsProject documentationProject risk analysisProject closureManagement and planning toolsBusiness results for projectsProcess performance CommunicationTeam dynamics and performanceTeam stages and dynamicsTeam roles and responsibilitiesTeam toolsTeam Communication Measure PhaseProcess analysis and documentationProbability and statisticsBasic probability conceptsCentral limit theorem, Statistical distributions, Collecting and summarizing dataTypes of data and measurement scalesSampling and data collection methodsDescriptive statisticsGraphical methodsMeasure Phase (contd E. Measurement system analysis (MSA) F. Process and performance capabilityProcess performance vs. process specificationsProcess capability studiesProcess capability (Cp, Cpk) and process performance (Pp, Ppk) indicesShort-term vs. long-term capability and sigma shift Analyze PhaseExploratory data analysisMulti-vari studiesCorrelation and linear regression B, Hypothesis testingBasics Tests for means, variances, and proportionsIntroduction to MINITAB Data analysis Improve Phase of Six SigmaDesign of experiments (DOE)Basic terms, DOE graphs, and plotsThe root cause analysisLean Tools 1. Waste elimination 2. Cycle-time reduction 3. Kaizen and kaizen blitz V1. Control PhaseStatistical process control (SPC)SPC BasicsRational subgroupingControl chartsControl planLean tools for process controlTotal productive maintenance (TPM)Visual factory Project Implementation & SupportMINITAB Practice and guidance for projectProject implementation supportTemplates and Toolkits application for Project workSupport on Data Project, Implementation and project completion BenefitsFrom the course Learn the principles and philosophy behind the Six Sigma technique Learn to apply statistical methods to improve business processes Design and implement Six Sigma projects in a practical scenario Learn the DMAIC process and various tools used in Six Sigma methodology Knowledge of Six Sigma Green Belt Professional enables you to understand real-world business problems, increase an organization's revenue by streamlining the process, and become an asset to an organization According to Villanova University, employers such as United Health Group, Honeywell, GE and Volkswagen have been actively seeking professionals with Six Sigma to fill a variety of positions The Training enhances your skills and enables you to perform roles like Quality Manager, Quality Analyst, Finance Manager, Supervisor, Quality Control, etc. According to Indeed.com, the national average salary for a Six Sigma Green Belt is $72,000 per year in the United States. From the workshop Instructor LED training by Six Sigma Black Belt and Master Belt experts to make candidate learn the real scenario of six sigma tools and methodology Learn the principles and philosophy behind the Six Sigma method Dummy project by instructors to make candidate get a hands-on six sigma projects Downloadable Six Sigma PPT & Six Sigma PDF Industry Based case studies High-Quality training from an experienced trainer The Program extensively uses Minitab, specialized statistical software. It provides you with a thorough knowledge of Six Sigma philosophies and principles (including supporting systems and tools). Know about six sigma certification cost and six sigma green belt certification cost. Who should attend? The Six Sigma program is designed for professionals and students who want to develop the ability to lead process improvement initiatives. Six Sigma tools and process is widely used in all business processes. Six Sigma is applicable in all industry and in all functional areas. An indicative list of participants in our Green Belt program could include: Financial/business analyst Commodity manager Project manager Quality manager Production manager Production Engineer Business development manager Manufacturing process engineer Continuous improvement director Business managers or consultants Project manager/Program Manager Director or VP of operations CEO, CFO, CTO Certification On successful completion of the course and course requisites, the candidate will receive Internationally recognized Six Sigma Green Belt Certification. This course offers Six Sigma Certification Validation Tool for Employers Your Six Sigma Certification Validation Tool can be used by employers, clients and other stakeholders to validate the authenticity of your Six Sigma Certifications you have received. Using the programming code located on your certified LSSGB certification, one can see all your training and certification details online.
Level 4 QLS Endorsed Course with FREE Certificate | CPD & CiQ Accredited | 120 CPD Points | Lifetime Access
Dive into the realm of Solar PV Systems Modelling and Analysis through EnergyEdge's course. Stay ahead in the field of renewable energy with expert training.
Duration 2 Days 12 CPD hours This course is intended for If you are a data analyst, data scientist, or a business analyst who wants to get started with using Python and machine learning techniques to analyze data and predict outcomes, this book is for you. Basic knowledge of computer programming and data analytics is a must. Familiarity with mathematical concepts such as algebra and basic statistics will be useful. Overview By the end of this course, you will have the skills you need to confidently use various machine learning algorithms to perform detailed data analysis and extract meaningful insights from data. This course is designed to give you practical guidance on industry-standard data analysis and machine learning tools in Python, with the help of realistic data. The course will help you understand how you can use pandas and Matplotlib to critically examine a dataset with summary statistics and graphs, and extract the insights you seek to derive. You will continue to build on your knowledge as you learn how to prepare data and feed it to machine learning algorithms, such as regularized logistic regression and random forest, using the scikit-learn package. You?ll discover how to tune the algorithms to provide the best predictions on new and unseen data. As you delve into later sections, you?ll be able to understand the working and output of these algorithms and gain insight into not only the predictive capabilities of the models but also their reasons for making these predictions. Data Exploration and Cleaning Python and the Anaconda Package Management System Different Types of Data Science Problems Loading the Case Study Data with Jupyter and pandas Data Quality Assurance and Exploration Exploring the Financial History Features in the Dataset Activity 1: Exploring Remaining Financial Features in the Dataset Introduction to Scikit-Learn and Model Evaluation Introduction Model Performance Metrics for Binary Classification Activity 2: Performing Logistic Regression with a New Feature and Creating a Precision-Recall Curve Details of Logistic Regression and Feature Exploration Introduction Examining the Relationships between Features and the Response Univariate Feature Selection: What It Does and Doesn't Do Building Cloud-Native Applications Activity 3: Fitting a Logistic Regression Model and Directly Using the Coefficients The Bias-Variance Trade-off Introduction Estimating the Coefficients and Intercepts of Logistic Regression Cross Validation: Choosing the Regularization Parameter and Other Hyperparameters Activity 4: Cross-Validation and Feature Engineering with the Case Study Data Decision Trees and Random Forests Introduction Decision trees Random Forests: Ensembles of Decision Trees Activity 5: Cross-Validation Grid Search with Random Forest Imputation of Missing Data, Financial Analysis, and Delivery to Client Introduction Review of Modeling Results Dealing with Missing Data: Imputation Strategies Activity 6: Deriving Financial Insights Final Thoughts on Delivering the Predictive Model to the Client
2 QLS Endorsed Course | CPD Certified | Free PDF + Hardcopy Certificates | 80 CPD Points | Lifetime Access
In this course you will learn how to use the power of Python to train your machine such that your machine starts learning just like human and based on that learning, your machine starts making predictions as well!