1118 Statistics courses in London delivered Online

Lean Six Sigma Green Belt Certification Program: On-Demand 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 - Become Green Belt Certified: On-Demand This course explores the DMAIC process in depth and enables you to achieve IIL's Lean Six Sigma Green Belt Certification. DMAIC is the foundation of Lean Six Sigma and process improvement. The incremental steps of "Define, Measure, Analyze, Improve, Control" give structure and guidance to improving quality, performance, and productivity. 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. 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 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 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 tests? Hypothesis tests Correlation and regression analysis 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 Result What is a pilot? Evaluating results 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

Session Border Controllers course description A hands on course covering Session Border Controllers with a focus on the technical workings of features commonly found in Session Border Controllers. Hands on practicals follow each major theory session. What will you learn Explain how Session Border Controllers work. Explain the SIP call flow using a SBC. Deploy Session Border Controllers Describe the features found in Session Border Controllers. Session Border Controllers course details Who will benefit: Technical staff working with SIP. Prerequisites: Definitive SIP for engineers Duration 2 days Session Border Controllers course contents SIP review Signalling, media, RTP, SIP, peer to peer, SIP proxies, SIP call flows. Hands on: SIP packet analysis. Session Border Controllers What is a SBC? SBC features, peering scenario, access scenario, NNI SBC, UNI SBC, enterprise SBC. Hands on: SBC call flows SBC topology hiding Header privacy, B2BUA. Hands on: Header analysis. Session control Call admissions, QoS, statistics and billing, redundancy and scalability. Hands on: SBC session control SBC and NAT NAT traversal, STUN, ICE, NAT and SIP, NAT and RTP. Hands on: SBC and NAT traversal. SBC and security DoS, access control, encryption, authentication, toll fraud, regulatory issues, lawful intercept. Hands on: Security. Interoperability mediation Manipulating SIP headers, IMS, IETF, TISPAN, SIP-I. SBC interworking.

Start your data science journey with this carefully constructed comprehensive course and get hands-on experience with Python for data science. Gain in-depth knowledge about core Python and essential mathematical concepts in linear algebra, probability, and statistics. Complete data science training with 13+ hours of content.

Ethernet LANS training course description This course has been replaced as part of our continuous curriculum development. Please see our Definitive Ethernet switching course What will you learn Describe what Ethernet is and how it works. Install Ethernet networks Troubleshoot Ethernet networks Analyse Ethernet packets Design Ethernet networks Recognise the uses of Hubs, Bridges, switches and routers. Ethernet LANS training course details Who will benefit: Those wishing to find out more about how their LAN works. Prerequisites: Intro to Data comms & networking. Duration 3 days Ethernet LANS training course contents What is Ethernet? LANS, What is Ethernet?, history, standards, the OSI reference model, how Ethernet works, CSMA/CD. Ethernet Cabling UTP, cat 3,4,5, Cat 5e, Cat 6, Cat 7, fibre optic cable, MMF, SMF. Hands on Making a cable. 802.3 physical specifications Distance limitations, hubs and repeaters, 5-4-3-2-1 rule, 10BaseT, 10BaseF, 100BaseTX, 100BaseFX, 1000BaseSX, 1000BaseT, 10gbe. Hands on Working with hubs. Ethernet layer 2 Overview, NICS, device drivers, MAC addresses, broadcasts, multicasts, frame formats, Ether II, 802.3, 802.2, SNAP, compatibility, Ethernet type numbers, Ethernet multicast addresses, Ethernet vendor codes. Hands on Installing Ethernet components, analysing MAC headers. IP and Ethernet ARP Hands on Analysing ARP packets. Ethernet extensions Full/half duplex, auto negotiation, flow control methods, 802.3ad, 802.3af, 802.3ah. Hands on Configuration of full/half duplex. Ethernet speed enhancements Encoding, Carrier extension, packet bursting, jumbo frames. Prioritisation 802.1P, 802.1Q, TOS, WRR, QOS, VLANs. Hands on 802.1p testing Interconnecting LANS Broadcast domains, Collision domains, What are bridges, transparent bridging, What are switches? STP, VLANS, What are routers? Layer 3 switches, Connecting Ethernet to the WAN. Hands on STP, Analysing Ethernet frames in a routed architecture. Troubleshooting and maintaining Ethernet Utilisation, performance, TDR and other testers, bottlenecks, statistics, RMON. Hands on Monitoring performance, troubleshooting tools.

About this course This practical course will help primary teachers to understand the purpose of assessment in history and consider current best practice. We will explore ways of continuing to improve the quality of teaching and learning in history through effective assessment strategies. We will go through practical ideas and resources to enliven teaching and learning in history and provide opportunities for assessment. This course will provide guidance and support to help develop the accuracy of teacher judgements. During the course, we will look at examples of writing and outcomes from different schools and consider how these outcomes demonstrate progress and attainment in history. Outcomes • understand the purpose of assessment in history • consider current best practice • explore ways of continuing to improve the quality of teaching and learning in history through effective assessment strategies • explore practical ideas and resources to enliven teaching and learning in history and provide opportunities for assessment • provide guidance and support to help develop the accuracy of teacher judgements Course leader The course is led by Steven Kenyon. Steven is a member of the Historical Association’s primary committee, having worked as a primary school teacher and then Deputy Head Teacher between 2004 and 2018. He joined Lancashire Professional Development Service in April 2018 as a Teaching and Learning Consultant for Primary History and English. He works closely with Lancashire Archives to promote and develop local history work in primary schools. This year he is a judge for the Historical Association's Young Quills Awards.

About Course Master the statistical skills you need to understand and analyze biomedical research data with this Biostatistics Online Course Are you working on public health, clinical medicine, biology or related fields? Are you familiar with the process of obtaining an accurate picture from a large number of data points? This Biostatistics Online Course demonstrates how to use statistical techniques to summarize the characteristics of a data set to draw meaningful conclusions. In this course, you will learn all about Biostatistics and its application in medical and life sciences. This course is a comprehensive introduction to the field of biostatistics, covering a wide range of topics from basic statistical concepts to more advanced biostatistical methods.Biostatistics Online Course modules: Module 1: Introduction to Biostatistics This module provides an overview of biostatistics, its applications in the field of health sciences, and the different types of study designs used in biomedical research. It also introduces the basic concepts of statistics, including data types, variables, inferential statistics, hypothesis testing, and the role of statistics in biostatistics and evidence-based medicine. Module 2: Probability This module covers the basics of probability, including probability distributions, random variables, and sampling distributions. Students will learn how to calculate and interpret probabilities in the context of biomedical research. Module 3: Descriptive Statistics This module covers the different measures of central tendency and variability, as well as graphical representations of data. Students will learn how to describe and summarize data from biomedical studies using these methods. Module 4: Inferential Statistics This module covers the fundamental concepts of inferential statistics, including estimation, hypothesis testing, confidence intervals, and p-values. Students will learn how to use these methods to draw conclusions about populations based on data from samples. Module 5: Regression Analysis This module introduces the basics of regression analysis, including simple linear regression, multiple linear regression, and logistic regression. Students will learn how to use these methods to model relationships between variables and to make predictions. Module 6: Biostatistics Tools This module covers a variety of biostatistical tools that are commonly used in biomedical research, including survival analysis, clinical trials, and epidemiological studies. Students will learn how to use these tools to answer specific research questions. Module 7: Statistical Software and Tools This module introduces students to popular statistical software programs, such as R and SPSS. Students will learn how to import, manage, and analyze data using these software programs, as well as how to perform statistical tests and generate summary statistics. Module 8: Ethical Considerations and Reporting Guidelines This module covers the importance of ethical considerations in biostatistics and the reporting guidelines for statistical analysis in research publications. Students will also learn about best practices for data management and data sharing. Why You Should Take This Course Whether you are a student, researcher, or healthcare professional, biostatistics is an essential skill for understanding and interpreting biomedical research. This course provides a comprehensive and accessible introduction to the field of biostatistics, covering all the essential topics that you need to know. By taking this course, you will learn how to: Design and conduct biomedical studies Collect and manage data Analyze data using statistical methods Interpret statistical results Communicate statistical findings effectively This course is ideal for students in the fields of public health, medicine, nursing, epidemiology, and other health sciences. It is also beneficial for researchers, healthcare professionals, and anyone else who wants to learn more about biostatistics. Enroll today and start your journey to becoming a biostatistics expert! To find more course in this topic, search more . What Will You Learn? Design and conduct biomedical studies Collect and manage data Analyze data using statistical methods Interpret statistical results Communicate statistical findings effectively Course Content Introduction to Biostatistics Introduction to Biostatistics Probability Module 2 Probability Descriptive Statistics Descriptive Statistics Inferential Statistics Inferential Statistics Regression Analysis Regression Analysis Biostatistics Tools Biostatistics Tools Statistical Software and Tools Statistical Software and Tools Ethical Considerations and Reporting Guidelines Ethical Considerations and Reporting Guidelines A course by Xpert Learning RequirementsBasic understanding of Mathematics and Statistics Audience Students in health sciences Researchers Healthcare professionals Anyone interested in learning about biostatistics Audience Students in health sciences Researchers Healthcare professionals Anyone interested in learning about biostatistics

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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.

Dive into the world of numbers and patterns with our 'Statistical Analysis Course,' where data tells stories and predictions shape the future. In the first module, you're introduced to the vast landscape of statistics, a toolset essential for deciphering the tales hidden within data. As you progress, familiarise yourself with the fundamental statistical terminology, paving the way for a deeper grasp of how data clusters around central values. The journey through this course is a blend of theory and application, from mastering the intricacies of data variability to the advanced realms of regression analysis and predictive algorithms. Learning Outcomes Gain a solid understanding of statistics and its significance in various fields. Learn to describe and utilise basic statistical terminology and methods. Comprehend and calculate measures of central tendency and data dispersion. Develop skills in probability, distribution analysis, and statistical inference. Apply statistical methods correctly and appreciate the Bayesian approach for learning from data. Why choose this Statistical Analysis Course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments are designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Statistical Analysis Course Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Who is this Statistical Analysis Course for? Aspiring data analysts seeking a foundation in statistics. Business professionals who require analytical skills for data-driven decision-making. Students of the social sciences, economics, or any field involving data interpretation. Researchers needing a robust grasp of statistical analysis methods. Anyone interested in understanding how to utilise data for predictions and analytics. Career path Data Analyst - £25,000 to £40,000 Market Research Analyst - £23,000 to £35,000 Quantitative Analyst - £35,000 to £70,000 Statistical Researcher - £27,000 to £45,000 Business Intelligence Analyst - £30,000 to £55,000 Econometrician - £30,000 to £60,000 Prerequisites This Statistical Analysis Course does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Statistical Analysis Course was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Course Curriculum Module 01: The Realm of Statistics The Realm Of Statistics 00:26:00 Module 02: Basic Statistical Terms Basic Statistical Terms 00:41:00 Module 03: The Center of the Data The Center of the Data 00:03:00 Module 04: Data Variability Data Variability 00:15:00 Module 05: Binomial and Normal Distributions Binomial and Normal Distributions 00:14:00 Binomial Probabilities Table 00:00:00 Z-Table 00:00:00 Module 06: Introduction to Probability Introduction to Probability 00:35:00 Module 07: Estimates and Intervals Estimates and Intervals 00:34:00 Module 08: Hypothesis Testing Hypothesis Testing 00:31:00 Module 09: Regression Analysis Regression Analysis 00:11:00 Module 10: Algorithms, Analytics and Predictions Algorithms, Analytics and Prediction 00:47:00 Module 11: Learning From Experience: The Bayesian Way Learning From Experience: The Bayesian Way 00:31:00 Module 12: Doing Statistics: The Wrong Way Doing Statistics: The Wrong Way 00:37:00 Module 13: How We Can Do Statistics Better How We Can Do Statistics Better 00:41:00 Assignment Assignment - Statistical Analysis Course 00:00:00