30749 Courses delivered Online

Monthly online ekphrastic writing workshops exploring contemporary artworks for story inspiration.

Are you interested in enrolling on an Online (Distance) Learning Degree at Arts University Plymouth, but curious about how virtually attending an Arts University works? If so, join us online for our Free 3-Session Online Learning Taster Course. An introduction to our January-start degrees. This course has been designed to give you a taste of what it is like to study with us virtually, as well as giving you tailored support for your university application. You will get a virtual art university experience, and a chance to meet some of the lecturers for the subjects you are interested in studying.

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

Online Asset Management Diploma course. Sit the IAM Diploma anywhere in the world. February to March 2024

Course Overview The comprehensive Online American Sign Language has been designed by industry experts to provide learners with everything they need to enhance their skills and knowledge in their chosen area of study. Enrol on the Online American Sign Language today, and learn from the very best the industry has to offer! This best selling Online American Sign Language has been developed by industry professionals and has already been completed by hundreds of satisfied students. This in-depth Online American Sign Language is suitable for anyone who wants to build their professional skill set and improve their expert knowledge. The Online American Sign Language is CPD-accredited, so you can be confident you're completing a quality training course which will boost your CV and enhance your career potential. The Online American Sign Language is made up of several information-packed modules which break down each topic into bite-sized chunks to ensure you understand and retain everything you learn. After successfully completing the Online American Sign Language, you will be awarded a certificate of completion as proof of your new skills. If you are looking to pursue a new career and want to build your professional skills to excel in your chosen field, the certificate of completion from the Online American Sign Language will help you stand out from the crowd. You can also validate your certification on our website. We know that you are busy and that time is precious, so we have designed the Online American Sign Language to be completed at your own pace, whether that's part-time or full-time. Get full course access upon registration and access the course materials from anywhere in the world, at any time, from any internet-enabled device.  Our experienced tutors are here to support you through the entire learning process and answer any queries you may have via email.

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 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

Online Asset Management Diploma course. Sit the IAM Diploma anywhere in the world

https://linktr.ee/drawtoperform

A practical approach to Data Governance, giving you the information you need to design and implement successfully a Data Governance Framework that is right for your organisation.