27648 OV courses delivered Online

This session will provide a clear update for governors as to the latest developments in terms of risk, updates on statutory guidance and KCSIE requirements from the governance perspective, and an overview of what the safeguarding team should be working on.

Duration 3 Days 18 CPD hours This course is intended for Senior Consultants (both functional and technical) that aspire to be Solution Architects, or current Solution Architects that are new to the role. The Solution Architect is responsible for the successful design, implementation, deployment and adoption of an overall solution. The Solution Architect ensures that the solution meets the customer?s needs now and in the future. In this course, students will learn about decisions a Solution Architect makes during an implementation, covering security, integrations, Power Apps architecture, Power Automate architecture, and more. This course is designed to give you an introduction to the Solution Architect role. Becoming a Solution Architect/Getting to know your customer Define a Solution Architect Role of a Solution Architect on projects Project Methodology Getting to know your customer Group exercise - Getting to know your customer Conceptualizing the design from requirements How to lead the requirement collection effort Using fit gap analysis Pillars of good architecture Blueprinting the solution architecture Group exercise - Design from requirements Project governance and working as a team Solution Architect's role in project governance Techniques for keeping a project on track Scenarios that could cause a project to fail Group exercise - Project governance and working as a team Power Platform Architecture Key Power Platform architecture components Understand how platform design and limits influence solution architectures Updates and feature releases Understand how to communicate how the platform meets customer needs Data Modeling Data model influences Data model strategy Data types Data relationships Group exercise - Data modeling Analytics and artificial intelligence Planning and evaluating requirements Operational reporting Power BI Enterprise BI Pre-built insights and custom AI Power Apps Architecture Discuss options for apps and how to choose where to start Discuss app composition options Using components as part of your app architecture Considerations for including Portals as an app in your architecture Group exercise - Power Apps Architecture topics Application Lifecycle Management (ALM) Microsoft vision and Solution Architect's role in ALM Environment strategies Defning a solution structure for your deliverable Power Automate Architecture Discuss options for automation and custom logic Review considerations for using triggers and common actions Explore using Business Process Flows (BPF) to guide users through business processes Group Exercise - Evaluate scenarios for Power Automate usage Security Modeling Solution Architect's role in security modeling Discovery and learning your client's environment Controlling access to environments and resources Controlling access to CDS Data Group Exercise - Security Modeling Integration Solution Architects role in Integrations What is an integration and why do we need it Platform features that enable integration CDS Event Publishing Scenarios for group discussion Dynamics 365 Applications Architecture Solution Architect's role when deploying Dynamics 365 apps Architecture Considerations for primary apps Group Exercise - App specific working groups evaluate requirements Power Virtual Agents architecture Introduction Chatbot options Chatbot concepts Best practices Integrate chatbots Power Virtual Agents in Microsoft Teams Robotic Process Automation Introduction Power Automate Desktop Recording and editing tasks Running desktop flows Process advisor Testing and Go Live Solution Architect's role with testing and go live Planning for testing Planning for go live

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

The ‘Mastering Management Fundamentals Open Programme’ is a 5 module online course that is designed to improve your management success and performance. It will give you the practical tools and insight to be able to make changes and directly improve your management skills over a 5-6 month period.

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

FAA Level 1 Award In Awareness Of Safeguarding (RQF) Face-to-Face Classroom: Half-day course Virtual Classroom: 2 sessions of 2 ½ hours For those who work with children, young people and vulnerable adults Promotes awareness of safeguarding, enabling learners to identify problems and show where to report these to Course Contents: Safeguarding legislation and guidance Key safeguarding roles Different types of abuse Signs and indicators of abuse and neglect Actions to take when a safeguarding concern arises Benefits of this course: In 2018/2019, 415,050 concerns of abuse were raised In 2018/2019, there were nearly 400,000 children in need 52,300 children were subject to a child protection plan 63% of adult safeguarding concerns are for people over 65 1 in every 42 adults aged 85+ have required safeguarding enquires... Child abuse often goes unreported and unrecorded - till it is picked up on by someone who then does something about it. This Level 1 Safeguarding Awareness course gives people the knowledge to make a real difference to a person's life! This basic Safeguarding course is a nationally recognised, Ofqual regulated qualifications accredited by First Aid Awards Ltd. This means that you can be rest assured that your Level 1 in Safeguarding Certificate provides information for best practice to make a real difference to protect the health and wellbeing of the most vulnerable in our society. The Ofqual Register number for this course is 603/5635/2

The purpose of these qualifications is to enable learners to coach clients – one to one and in small groups – towards their health and fitness goals. Learners will develop the knowledge, skills and behaviours to plan and deliver creative and personalised exercise programmes, provide nutritional advice and support clients with their overall lifestyle management.

Whetstone Communications and comms2point0 are pleased to bring you the Data Bites series of free webinars. Our aim is to boost interest and levels of data literacy among not-for-profit communicators.

At the end of the 5 days, Learners will attain an RQF Award in the requirements of FD&FA systems for non-domestic buildings BS 5839-1: 2017.

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