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EFQM Performance Improvement Practitioner Course A 2-day deep-dive workshop on RADAR and how to use it as an agile project performance framework. The essential course for anyone wanting to learn more about the RADAR logic and how to build a continuous improvement culture and mindset across your whole organisation.   Who is it for? This course is suitable for anyone who wants to understand the RADAR logic and how it can be used to make their organisation more effective. Whilst this training is effective as a stand-alone course; it is also a Level 1 option for anyone considering one of the EFQM qualification routes as a way of progressing their management development and career.   Benefits By the end of the course, participants will be able to: Explain the overall RADAR logic Explain the main principles of positive culture and mindset for driving performance Describe how RADAR can be implemented into an organisation to improve performance at every level Identify how to use RADAR to drive the management agenda Apply RADAR across day-to-day initiatives and key projects as an agile project performance framework. Programme The main topics covered during the EFQM Performance Improvement Practitioner training are: RADAR logic and examples of how it can be used Using RADAR to drive the management agenda Using RADAR to drive strategic initiatives Using RADAR to set up strategic KPI’s RADAR as a Performance Improvement Framework Case studies and group exercises RADAR Improvement Matrix self-assessment The training is spread over two days and is delivered in a virtual classroom setting (Zoom or Microsoft Teams), using videos, group discussions, case studies and activities in breakout rooms and presentations from the trainer.   Further Development The EFQM Performance Improvement Practitioner training provides core knowledge about the RADAR Logic. In some cases, the training will have fulfilled an individual's learning needs. In many cases, the individual will want to consolidate their learning by applying the theory to a practical task. We encourage you to apply RADAR to a practical, work-based project, and we provide guidance on how to approach and complete your project.    Completion of the RADAR Performance Improvement Project also allows you to progress to one of the advanced EFQM qualification programmes: EFQM Performance Improvement Leader, EFQM Assessor or EFQM Organisational Change Leader.   EFQM Performance Improvement Leader If you successfully complete the EFQM Performance Improvement Practitioner training and the subsequent project, you are invited to apply for the EFQM Performance Improvement Leader assessment. You will be guided and coached by an EFQM trainer and asked to present your project to the EFQM expert panel. Here you will answer questions about how you applied the RADAR logic and principles (we provide participants with templates for running the project, as well as a high-level mid-term review). You will also receive feedback on how to improve and maximise the use of RADAR for future endeavours. Dates and time: This is a two day on-line workshop delivered on the 12th of June & 18th of June from 9:00 AM to 3:30 PM GMT Cost: £1000 + VAT

This half-day workshop delivered face-to-face or online is designed for anyone in your organisation that wants to become a Neurodiversity Champion - someone who wants to educate and change the way that Neurodiversity is viewed in the workplace.

Learn and practice the skills needed to deliver a brilliant presentation.

Duration 4 Days 24 CPD hours This course is intended for This course is intended for: Developers Solutions Architects Data Engineers Anyone with little to no experience with ML and wants to learn about the ML pipeline using Amazon SageMaker Overview In this course, you will learn to: Select and justify the appropriate ML approach for a given business problem Use the ML pipeline to solve a specific business problem Train, evaluate, deploy, and tune an ML model using Amazon SageMaker Describe some of the best practices for designing scalable, cost-optimized, and secure ML pipelines in AWS Apply machine learning to a real-life business problem after the course is complete This course explores how to use the machine learning (ML) pipeline to solve a real business problem in a project-based learning environment. Students will learn about each phase of the pipeline from instructor presentations and demonstrations and then apply that knowledge to complete a project solving one of three business problems: fraud detection, recommendation engines, or flight delays. By the end of the course, students will have successfully built, trained, evaluated, tuned, and deployed an ML model using Amazon SageMaker that solves their selected business problem. Module 0: Introduction Pre-assessment Module 1: Introduction to Machine Learning and the ML Pipeline Overview of machine learning, including use cases, types of machine learning, and key concepts Overview of the ML pipeline Introduction to course projects and approach Module 2: Introduction to Amazon SageMaker Introduction to Amazon SageMaker Demo: Amazon SageMaker and Jupyter notebooks Hands-on: Amazon SageMaker and Jupyter notebooks Module 3: Problem Formulation Overview of problem formulation and deciding if ML is the right solution Converting a business problem into an ML problem Demo: Amazon SageMaker Ground Truth Hands-on: Amazon SageMaker Ground Truth Practice problem formulation Formulate problems for projects Module 4: Preprocessing Overview of data collection and integration, and techniques for data preprocessing and visualization Practice preprocessing Preprocess project data Class discussion about projects Module 5: Model Training Choosing the right algorithm Formatting and splitting your data for training Loss functions and gradient descent for improving your model Demo: Create a training job in Amazon SageMaker Module 6: Model Evaluation How to evaluate classification models How to evaluate regression models Practice model training and evaluation Train and evaluate project models Initial project presentations Module 7: Feature Engineering and Model Tuning Feature extraction, selection, creation, and transformation Hyperparameter tuning Demo: SageMaker hyperparameter optimization Practice feature engineering and model tuning Apply feature engineering and model tuning to projects Final project presentations Module 8: Deployment How to deploy, inference, and monitor your model on Amazon SageMaker Deploying ML at the edge Demo: Creating an Amazon SageMaker endpoint Post-assessment Course wrap-up Additional course details: Nexus Humans The Machine Learning Pipeline on AWS training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the The Machine Learning Pipeline on AWS course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 4 Days 24 CPD hours This course is intended for This course is designed for data scientists with existing knowledge of Python and machine learning frameworks like Scikit-Learn, PyTorch, and Tensorflow, who want to build and operate machine learning solutions in the cloud. Overview Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring in Microsoft Azure. Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring with Azure Machine Learning and MLflow. Prerequisites Creating cloud resources in Microsoft Azure. Using Python to explore and visualize data. Training and validating machine learning models using common frameworks like Scikit-Learn, PyTorch, and TensorFlow. Working with containers AI-900T00: Microsoft Azure AI Fundamentals is recommended, or the equivalent experience. 1 - Design a data ingestion strategy for machine learning projects Identify your data source and format Choose how to serve data to machine learning workflows Design a data ingestion solution 2 - Design a machine learning model training solution Identify machine learning tasks Choose a service to train a machine learning model Decide between compute options 3 - Design a model deployment solution Understand how model will be consumed Decide on real-time or batch deployment 4 - Design a machine learning operations solution Explore an MLOps architecture Design for monitoring Design for retraining 5 - Explore Azure Machine Learning workspace resources and assets Create an Azure Machine Learning workspace Identify Azure Machine Learning resources Identify Azure Machine Learning assets Train models in the workspace 6 - Explore developer tools for workspace interaction Explore the studio Explore the Python SDK Explore the CLI 7 - Make data available in Azure Machine Learning Understand URIs Create a datastore Create a data asset 8 - Work with compute targets in Azure Machine Learning Choose the appropriate compute target Create and use a compute instance Create and use a compute cluster 9 - Work with environments in Azure Machine Learning Understand environments Explore and use curated environments Create and use custom environments 10 - Find the best classification model with Automated Machine Learning Preprocess data and configure featurization Run an Automated Machine Learning experiment Evaluate and compare models 11 - Track model training in Jupyter notebooks with MLflow Configure MLflow for model tracking in notebooks Train and track models in notebooks 12 - Run a training script as a command job in Azure Machine Learning Convert a notebook to a script Run a script as a command job Use parameters in a command job 13 - Track model training with MLflow in jobs Track metrics with MLflow View metrics and evaluate models 14 - Perform hyperparameter tuning with Azure Machine Learning Define a search space Configure a sampling method Configure early termination Use a sweep job for hyperparameter tuning 15 - Run pipelines in Azure Machine Learning Create components Create a pipeline Run a pipeline job 16 - Register an MLflow model in Azure Machine Learning Log models with MLflow Understand the MLflow model format Register an MLflow model 17 - Create and explore the Responsible AI dashboard for a model in Azure Machine Learning Understand Responsible AI Create the Responsible AI dashboard Evaluate the Responsible AI dashboard 18 - Deploy a model to a managed online endpoint Explore managed online endpoints Deploy your MLflow model to a managed online endpoint Deploy a model to a managed online endpoint Test managed online endpoints 19 - Deploy a model to a batch endpoint Understand and create batch endpoints Deploy your MLflow model to a batch endpoint Deploy a custom model to a batch endpoint Invoke and troubleshoot batch endpoints

Duration 1 Days 6 CPD hours This course is intended for This course is intended for individuals who want to develop a core set of soft skill. Overview Upon successful completion of this course, students will be able to better interact and communicate in the workplace. In this course, students will develop a core set of soft skills by managing and looking at the way people interact and seeing things in a new light. 1 - GETTING STARTED Housekeeping Items Pre-Assignment Review Workshop Objectives The Parking Lot Action Plan 2 - WHAT ARE SOFT SKILLS? Definition of Soft Skills Empathy and the Emotional Intelligence Quotient Professionalism Learned vs. Inborn Traits 3 - SOFT SKILL 1: COMMUNICATION Ways We Communicate Improving Non-Verbal Communication Listening Openness and Honesty 4 - SOFT SKILL 2: TEAMWORK Identifying Capabilities Get Into Your Role Learn the Whole Process The Power of Flow 5 - SOFT SKILL 3: PROBLEM SOLVING Define the Problem Generate Alternative Solutions Evaluate the Plans Implementation and Re-evaluation 6 - SOFT SKILL 4: TIME MANAGEMENT The Art of Scheduling Prioritizing Managing Distractions The Multitasking Myth 7 - SOFT SKILL 5 AND 6: ATTITUDE AND WORK ETHIC What Are You Working For? Caring for Others vs. Self Building Trust Work Is Its Own Reward 8 - SOFT SKILL 7: ADAPTABILITY/FLEXIBILITY Getting over the Good Old Days Syndrome Changing to Manage Process Changing to Manage People Showing You're Worth Your Weight in Adaptability 9 - SOFT SKILL 8: SELF-CONFIDENCE Confident Traits Self-Questionnaire Surefire Confidence Building Tactics Build Up Others 10 - SOFT SKILL 9: ABILITY TO LEARN FROM CRITICISM Wow, You Mean I'm Not Perfect? Listen With An Open Mind Analyze and Learn Clear the Air and Don't Hold Any Grudges 11 - SOFT SKILL 10: NETWORKING Redefining Need Identifying Others' Interests Reaching Out When to Back Off 12 - WRAPPING UP Words From The Wise Review Of The Parking Lot Lessons Learned Recommended Reading Completion Of Action Plans And Evaluations Additional course details: Nexus Humans 10 Soft Skills You Need training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the 10 Soft Skills You Need course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

This highly interactive workshop will give your management team the skills and the tools necessary to understand relationships and behavioral styles of employees, improve performance and efficiency, and adopt solutions and strategies to increase your competitive edge. Optimised for tailored audiences Built for groups of 20+ Led by experienced and certified professionals Specialised to address issues around inclusivity and equity in all industries Program Details Peak Performance Part I: Observation, Assessment and Determination The final objective of this workshop is a full understanding of how managers can assess their employees for optimal behavioral team communication and assignments. Peak Performance Part II: High Efficiency Teams The final objective of this workshop is a full understanding of how managers can create High Efficiency teams taking into accounts skills and behaviors. Peak Performance Part III: Self-Learning Teams The Final objective of this workshop is KPIs agreed upon and commonly shared by employees and managers to allow employees to self-manage their learning and measure their progress monitored by managers. Investment Fee: £50,000 25 participants max per 12-week cohort TRAINING FORMAT : 12 - Week Cohorts Delivered in 1-hour sessions Virtually Facilitated Sessions Corporate Peak Performance Program One Pager

This Digital Electronics Course is designed to give practical knowledge of the type of electronic circuitry used in a modern Computer System or in any type of Computer Controlled equipment such as Photocopiers, Cash Registers, Tablets, mobile phones and many other types of IT equipment. Digital Electronics involves the use of Silicon chips (Integrated Circuits). The internal structure of a computer is to a large extent comprised of Digital Electronic Circuits.

Discover how to elevate your career as an executive assistant or personal assistant with our comprehensive EA Mastery Workshop. Gain new skills, strategies, and tools to maximize your impact and achieve success.

Insightful leaders understand the importance of employee collaboration and a solid team ethos. Highly efficient and self-learning teams only achieve top performance when leaders and team members are aligned with regard to diversity, equity and inclusion. This is a highly interactive and tailored workshop with two tracks: Upper Management Track and Midde Management/Staff Track. Optimised for tailored audiences Built for groups of 20+ Led by experienced and certified professionals Specialised to address issues around inclusivity and equity in all industries Program Details For Upper Management Teams Module 1 – The Empowered Leader: 15 Characteristics Module 2 – Communication and Listening Skills Module 3 – Empowering and Respecting Employees Module 4 – (DEI) Principles for Full Cultural Inclusivity For Middle Management & Staff Teams Module 1 – Typical Struggles Module 2 – Support for Growth Module 3 – Get Inspired Module 4 – See What it Looks Like Investment Fee: £50,000 25 participants max per 12-week cohort TRAINING FORMAT : 16 - Week Cohorts Delivered in 1-hour sessions Virtually Facilitated Sessions Corporate DEI Program One Pager