40148 Courses

You MUST complete E-Learning on The Oliver McGowan Mandatory Training On Learning Disabilites & Autism before you attend further training. This is free and can be accessed here: https://portal.e-lfh.org.uk/Component/Details/781480 The training contains potentially challenging material that mentions death and dying, trauma, mental and physical illness, system failures and inequalities faced by autistic people and people with a learning disability. Tier 2 - Train The Facilitator Course Information  Suitable For: People who have the skills and experience needed to deliver Tier 2 Face-to-Face training to trainees who provide support and/or care of autistic people or people with a learning disability. Course Summary:  Tier 2 Train The Facilitator is a 2 day course. Trainee Facilitators need to: Complete the E-learning Attend a live Tier 2 training session Day 1 - Learning Disability Training Day Day 2 - Autism Training Day The trainee will then be assessed by our Lead Trainer where a decision will be made regarding signing the trainee off to delivery training. Information about The Oliver McGowan Mandatory Training on Learning Disabilities & Autism The training is named after Oliver McGowan. Oliver was a young man whose death at the age of 18, shone a light on the need for health and social care colleagues to have better skills, knowledge and understanding of the needs for autistic people and people with a learning disability. The Oliver McGowan Mandatory Training on Learning Disability and Autism is the government’s preferred and recommended training for health and social care staff and is enshrined in law in the Health & Care Act 2022. The Oliver McGowan Mandatory Training on Learning Disability and Autism is co-delivered with a Facilitator and co-trainers with lived experience of learning disability and autism. The Oliver McGowan Mandatory Training is a standardised package that is delivered by trained and approved trainers. The consistent content and delivery means it is transferable between employers. Content may trigger difficult and upsetting feelings. Please note that for this course to run there is a minimum of 3 trainees to attend; if this is not met by the day before the course it may not go ahead and you will need to reschedule.

Official BRCGS Packaging Sites Issue 6 course. Delivered online (Zoom) by a live BRCGS Approved Training Partner. Exam and Certificate fee included in the price.

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

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Duration 5 Days 30 CPD hours This course is intended for Candidates for this course design, develop, secure, and troubleshoot Power Platform solutions. Candidates implement components of a solution that include application enhancements, custom user experience, system integrations, data conversions, custom process automation, and custom visualizations. Candidates will gain applied knowledge of Power Platform services, including in-depth understanding of capabilities, boundaries, and constraints. Overview After completing this course, students will be able to: Create a technical design Configure Common Data Service Create and configure Power Apps Configure business process automation Extend the user experience Extend the platform Develop Integrations The Microsoft Power Platform helps organizations optimize their operations by simplifying, automating and transforming business tasks and processes. In this course, students will learn how to build Power Apps, Automate Flows and extend the platform to complete business requirements and solve complex business problems. Create a model-driven application in Power Apps This module introduces you to creating a model-driven app in Power Apps that uses Common Data Service. Get started using Common Data Service This module will explain the concepts behind and benefits of Common Data Service. Creating an environment, entities, fields and options sets are also discussed. Create a canvas app in Power Apps This module introduces you to Power Apps, helps you create and customize an app, and then manage and distribute it. It will also show you how to provide the best app navigation, and build the best UI using themes, icons, images, personalization, different form factors, and controls. Automate a business process using Power Automate This module introduces you to Power Automate, teaches you how to build workflows, and how to administer flows. Create a business process flow in Power Automate This module introduces you to creating business process flows in Power Automate Introduction to developing with Power Platform This module is the first step in learning about platform, tools, and the ecosystem of the Power Platform Extending the Power Platform user experience Model Driven apps This module describes how to create client scripting, perform common actions with client script, and automate business process flow with client scrip. Learn about what client script can do, rules, and maintaining scripts. Discover when to use client script as well as when not to use client script. Create components with Power Apps Component Framework This module describes how to get started with Power Apps Component Framework with an introductory module on the core concepts and components. Then it shows you how to build a component and work with advanced Power Apps Component Framework features. Extending the Power Platform Common Data Service This module looks at the tools and resources needed for extending the Power Platform. We'll start with looking at the SDKs, the extensibility model, and event framework. This learning path also covers when to use plug-ins. Configuration of plug-ins as well as registering and deploying plug-ins. Integrate with Power Platform and Common Data Service This module describes how to integrate with Common Data Service using code by learning about Common Data Service API. Get an in-depth overview of options available with Common Data Service to integrate data and events to Azure. Extend Power Apps portals This module describes how to transform a content portal into a full web app interacting with Common Data Service. We will also cover the options available to customizers and developers to extend the portal functionality and integrate with Office 365, Power Platform, and Azure components. Additional course details: Nexus Humans PL-400T00 Microsoft Power Platform Developer 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 PL-400T00 Microsoft Power Platform Developer 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.

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Platelet-rich Plasma (PRP) treatments Nationally Recognised Qualification No previous experience or qualifications needed Open College Network Accreditation Level 4 (as required for minimally invasive procedures) Covers standards set by HEE Employed (salon) or Self-Employed opportunities Basic understanding of English language required OPEN TO ALL APPLICANTS