2051 Courses in London

Agile Sprint Planning: In-House Training The goal of the course is to provide you and your team with the ability to develop effective and realistic Sprint plans. Without effective Sprint Plans, iterations are set up for failure. But Sprint Planning cannot be improved on its own, in isolation. The Scrum processes are highly intertwined and influence each other. The surrounding artifacts, events, and roles must be examined closely, and enhanced, in order to improve Sprint Planning. This course will remind you of the theory to reinforce the principles, but will concentrate on next-level skills, so that you and the team are able to create realistic and usable Sprint Plans. This course is not introductory. You are already aware of the Scrum framework and have been implementing Scrum on your projects. Now is the time to improve efficiency and effectiveness, to facilitate successful Agile projects. What you will Learn You'll learn how to: Identify and correlate the key symptoms and root causes of ineffective sprint plans Improve key Product Backlog elements Evaluate Agile roles in sprint planning Appraise key product practices Enhance project transparency The Product Backlog User stories Acceptance Criteria Backlog Refinement Supporting Roles Product Owner (the Backlog) Development Team Stakeholders and SMEs Supporting Product Practices Roadmaps and release plans and story maps Definition of Done Technical Debt Transparency Daily Scrums Information radiators Retrospectives Sprint Planning Capacity and Velocity Sprint Planning Meetings The Sprint Backlog Summary What did we learn, and how can we implement this in our work environments?

CRRUK equips professionals with the concepts, skills and tools to build conscious, intentional relationships, and to coach relationship systems of any size.

Lean Six Sigma Yellow Belt Certification Program This course is designed to instill an in-depth understanding of Lean Six Sigma and a clear sense of what is required to define high-impact improvement projects, establish Lean Six Sigma measurements, and complete Lean Six Sigma projects using the systematic and proven Define, Measure, Analyze, Improve, and Control (DMAIC) methodology. This course is designed to instill an in-depth understanding of Lean Six Sigma and a clear sense of what is required to define high-impact improvement projects, establish Lean Six Sigma measurements, and complete Lean Six Sigma projects using the systematic and proven Define, Measure, Analyze, Improve, and Control (DMAIC) methodology. Participants will learn basic tools and techniques of Lean Six Sigma and those who pass a thirty-question exam (70% or above) will become a Certified Lean Six Sigma Yellow Belt. This course is delivered through four 3-hour online sessions. What you Will Learn You'll learn how to: Establish the structure that supports and sustains Lean Six Sigma Quality Identify and calculate key Lean Six Sigma Measurements (Sigma, DPMO, and Yield) Select successful, high-impact projects that match strategic objectives Document, measure, and improve key processes using the DMAIC (Define, Measure, Analyze, Improve, and Control) Methodology Utilize data-based thinking to make key business decisions Introduction to the Fundamentals and Vision of Lean Six Sigma Lean Six Sigma's focus on the customer, on quality, and on results The costs of poor quality Critical factors to consider when deploying Lean Six Sigma Lean Six Sigma as a process improvement methodology Lean Six Sigma metrics Why do it - ROI and payback for Lean Six Sigma Business Process Management Critical Lean Six Sigma roles and responsibilities Main aspects of managing the organizational change Project selection Metrics of Lean Six Sigma and the DMAIC Model How to strategically align business metrics and projects within an organization How to identify and measure quality characteristics which are critical to customers What does the customer (internal or external) really want from our products and services? Establishing appropriate teams and setting those teams up to be successful What defines a good measurement system? How are we doing (learning the secret to measuring the right things, right)? How to improve output measures by understanding and measuring the process Where are there defects (how to properly select and scope high-impact projects)? Where is the process broken (the Lean Six Sigma version of root cause analysis)? How to determine the process efficiency, or value add, of a process The appropriate use of quality tools Understanding the concept of variation and how to reduce knee-jerk reactions How to achieve breakthrough results for any key measure How can we ensure the identified improvements will be sustainable (the basics of process control)?

Lean Six Sigma Yellow Belt Certification Program: In-House Training This course is designed to instill an in-depth understanding of Lean Six Sigma and a clear sense of what is required to define high-impact improvement projects, establish Lean Six Sigma measurements, and complete Lean Six Sigma projects using the systematic and proven Define, Measure, Analyze, Improve, and Control (DMAIC) methodology. This course is designed to instill an in-depth understanding of Lean Six Sigma and a clear sense of what is required to define high-impact improvement projects, establish Lean Six Sigma measurements, and complete Lean Six Sigma projects using the systematic and proven Define, Measure, Analyze, Improve, and Control (DMAIC) methodology. Participants will learn basic tools and techniques of Lean Six Sigma and those who pass a thirty-question exam (70% or above) will become a Certified Lean Six Sigma Yellow Belt. This course is delivered through four 3-hour online sessions. What you Will Learn You'll learn how to: Establish the structure that supports and sustains Lean Six Sigma Quality Identify and calculate key Lean Six Sigma Measurements (Sigma, DPMO, and Yield) Select successful, high-impact projects that match strategic objectives Document, measure, and improve key processes using the DMAIC (Define, Measure, Analyze, Improve, and Control) Methodology Utilize data-based thinking to make key business decisions Introduction to the Fundamentals and Vision of Lean Six Sigma Lean Six Sigma's focus on the customer, on quality, and on results The costs of poor quality Critical factors to consider when deploying Lean Six Sigma Lean Six Sigma as a process improvement methodology Lean Six Sigma metrics Why do it - ROI and payback for Lean Six Sigma Business Process Management Critical Lean Six Sigma roles and responsibilities Main aspects of managing the organizational change Project selection Metrics of Lean Six Sigma and the DMAIC Model How to strategically align business metrics and projects within an organization How to identify and measure quality characteristics which are critical to customers What does the customer (internal or external) really want from our products and services? Establishing appropriate teams and setting those teams up to be successful What defines a good measurement system? How are we doing (learning the secret to measuring the right things, right)? How to improve output measures by understanding and measuring the process Where are there defects (how to properly select and scope high-impact projects)? Where is the process broken (the Lean Six Sigma version of root cause analysis)? How to determine the process efficiency, or value add, of a process The appropriate use of quality tools Understanding the concept of variation and how to reduce knee-jerk reactions How to achieve breakthrough results for any key measure How can we ensure the identified improvements will be sustainable (the basics of process control)?

Organisational retreat, organisational seminar, executive development,

This course shows you how to apply various approaches and algorithms to solve business problems through AI and ML, follow a methodical workflow to develop sound solutions, use open-source, off-the-shelf tools to develop, test, and deploy those solutions, and ensure that they protect the privacy of users. This course includes hands-on activities for each topic area.

Welcome to the combined course on : I. ISM (International Safety Management), /ISPS (International Ship and Port Facility Security), /MLC (Maritime Labour Convention)., II. ISO (International Organization for Standardization) standards (ISO 9001, ISO 14001, ISO 45001), This course aims to provide you with a comprehensive understanding of various maritime industry standards and regulations that play a crucial role in ensuring safety, security, environmental protection, and quality management in the maritime sector. I. ISM,ISPS,MLC Maritime Auditor The International Safety Management (ISM) Code sets guidelines for the safe operation of ships and pollution prevention. It establishes a framework for ship management and requires companies to develop and implement a Safety Management System (SMS) to ensure the safety of ships and personnel. The International Ship and Port Facility Security (ISPS) Code is a set of measures designed to enhance the security of ships and port facilities. It aims to detect security threats and take preventive measures to protect ships, ports, and the maritime supply chain from acts of terrorism, piracy, and other criminal activities. The Maritime Labour Convention (MLC) is an international labor standardthat sets out seafarers' rights and working conditions. It covers a wide rangeof issues, including employment contracts, working hours, accommodation, healthand safety, and welfare, ensuring that seafarers are treated fairly and provided with adequate working and living conditions. II. ISO (International Organization for Standardization) standards (ISO 9001, ISO 14001, ISO 45001) ISO standards, including ISO 9001 (Quality Management System), ISO 14001 (Environmental Management System), and ISO 45001 (Occupational Health and Safety Management System), provide internationally recognized frameworks for organizations to manage their quality, environmental, and occupational health and safety responsibilities. These standards help companies establish efficient processes, minimize risks, and improve their overall performance. Throughout this course, you will delve into each topic, exploring their principles, requirements, and best practices. By the end of this combined course, you will have gained valuable insights into the key aspects of maritime safety, security, labor standards, quality management, and the role of the Designated Person Ashore

This Beginners Barbering Course is aimed at those looking to be work-ready upon completion and working towards an internationally recognised Barbering qualification. After an initial induction, on day 2 you will learn to cut & style utilising the 5 Alan d Foundation haircuts before moving on to the practical elements of Barbering, incorporating all the latest techniques using scissors, scissor-over-comb, clippers & trimmers and learning beard and moustache trimming and wet shaving.

Unity 3d face to face training customised and bespoke.

This Python Machine Learning online instructor led course is an excellent introduction to popular machine learning algorithms. Python Machine Learning 2-day Course Prerequisites: Basic knowledge of Python coding is a pre-requisite. Who Should Attend? This course is an overview of machine learning and machine learning algorithms in Python SciKitLearn. Practical: We cover the below listed algorithms, which is only a small collection of what is available. However, it will give you a good understanding, to plan your Machine Learning project We create, experiment and run machine learning sample code to implement a short selected but representative list of available the algorithms. Course Outline: Supervised Machine Learning: Classification Algorithms: Naive Bayes, Decision Tree, Logistic Regression, K-Nearest Neighbors, Support Vector Machine Regression Algorithms: Linear, Polynomial Unsupervised Machine Learning: Clustering Algorithms: K-means clustering, Hierarchical Clustering Dimension Reduction Algorithms: Principal Component Analysis Latent Dirichlet allocation (LDA) Association Machine Learning Algorithms: Apriori, Euclat Other machine learning Algorithms: Ensemble Methods ( Stacking, bagging, boosting ) Algorithms: Random Forest, Gradient Boosting Reinforcement learning Algorithms: Q-Learning Neural Networks and Deep Leaning Algorithms: Convolutional Network (CNN) Data Exploration and Preprocessing: The first part of a Machine Learning project understands the data and the problem at hand. Data cleaning, data transformation and data pre-processing are covered using Python functions to make data exploration and preprocessing relatively easy. What is included in this Python Machine Learning: Python Machine Learning Certificate on completion Python Machine Learning notes Practical Python Machine Learning exercises and code examples After the course, 1 free, online session for questions or revision Python Machine Learning. Max group size on this Python Machine Learning is 4. Refund Policy No Refunds