2135 Courses in Edinburgh delivered Live Online

To drive actions and get decisions made, you need to be able to present effectively to customers, clients, senior managers or colleagues. The perfect presentation is a potent combination of content, design and delivery  You need to distill down complex concepts, large data sets, intricate processes and innovative ideas. You need to make the right design choices to ensure your slide decks communicate quickly (as well as looking great). And you need the confidence and storytelling techniques to lead your audience through the content.  This course is for anyone who regularly needs to create and deliver presentations for different stakeholders. It will cover how to plan, design and deliver brilliant presentations.  Sample learning content  Session 1: Planning a presentation  Assessing the needs and level of understanding of your audience. Frameworks for building a logical and compelling narrative. Emphasising key messages, while allowing for deep dives and questions. Session 2: Presenting data and processes Understand graphical perception and how people absorb visual information. Effective charts for different types of data stories. How to display processes, timelines and organisational structures. Session 3: Design tricks Using colours to add emphasis and meaning. Creating hierarchies of information to help your audience. Building templates and style guides. Session 4: Delivery techniques Perfecting your performance in-person or online. Dealing with difficult questions and hostile audiences. Refining the beginning, middle and end of your narrative. Delivery We deliver our courses over Zoom, to maximise flexibility. The training can be delivered in a single day, or across multiple sessions. All of our courses are live and interactive – every session includes a mix of formal tuition and hands-on exercises. To ensure this is possible, the number of attendees is capped at 16 people.  Tutor Alan Rutter is the founder of Fire Plus Algebra. He is a specialist in communicating complex subjects through data visualisation, writing and design. He teaches for General Assembly and runs in-house training for public sector clients including the Home Office, the Department of Transport, the Biotechnology and Biological Sciences Research Council, the Health Foundation, and numerous local government and emergency services teams. He previously worked with Guardian Masterclasses on curating and delivering new course strands, including developing and teaching their B2B data visualisation courses. He oversaw the iPad edition launches of Wired, GQ, Vanity Fair and Vogue in the UK, and has worked with Condé Nast International as product owner on a bespoke digital asset management system for their 11 global markets. Testimonial "We’ve now worked with Alan for almost 3 years, and during that time he has continued to deliver the highest quality training for our clients and delegates. Alan’s passionate delivery style has continued to deliver innovative training solutions to over 1500 delegates across the public, private and voluntary sector. Each of our courses with him has always delivered exceptional feedback and satisfaction levels." Joe Barlow | Head of Programme, Understanding ModernGov

Asbestos bulk analysts and laboratory analysts. Anyone who manages asbestos analysts or requires a deeper understanding of the asbestos analysis process (e.g. Laboratory Quality Manager) Prior Knowledge and Understanding Candidates for this course are expected to be aware of HSG 248 Asbestos: The Analysts' Guide (July 2021), and in particular Appendix 2: Determination of asbestos in bulk materials. Candidates will preferably have prior experience of analysing bulk samples and may already be participating in a quality control scheme. In addition, candidates are expected to have had training to cover the core competencies outlined within the foundation material detailed within Table A9.1 of HSG248 Asbestos: The Analysts' Guide (July 2021). This may be achieved by In -house learning or through the P400 foundation module.

Successful communications are all about making the message as simple as possible – but this can be difficult when the subjects we're talking about are inherently complicated.  Academic institutions, tech companies, health organisations, charities and many others have complex ideas, processes and systems at the heart of what they do.  This course is for anybody who needs to distill information down into key messages for important stakeholders, funders and investors, decision makers and members of the public.  You’ll learn proven techniques for grabbing attention and changing minds through presentations and public speaking, infographics and data visualisations, and written reports and online posts.  We’ll work with you before the course to ensure that we understand your organisation and what you’re hoping to achieve. Sample learning content Session 1: Understanding your audience Matching your objectives to your audience's motivations. Identifying the right tone and language. Understanding how, where and when your audience wants to be spoken to. Session 2: Refining your objectives  Breaking down strategic aims into tactical steps Metrics and milestones: defining and measuring progress and success. Rapidly building a brief for your communications. Session 3: Telling the story  Using metaphors, visuals, comparisons to frame your narrative. From slide decks to online campaigns - choosing the right formats for delivering your message. Selecting communications channels to maximise reach and impact. Session 4: Keeping it going  Processes and systems for launching and maintaining communications campaigns. Building social proof – creating and curating content. Troubleshooting and preparing for common challenges. Delivery We deliver our courses over Zoom, to maximise flexibility. The training can be delivered in a single day, or across multiple sessions. All of our courses are live and interactive – every session includes a mix of formal tuition and hands-on exercises. To ensure this is possible, the number of attendees is capped at 16 people.  Tutor Alan Rutter is the founder of Fire Plus Algebra. He is a specialist in communicating complex subjects through data visualisation, writing and design. He teaches for General Assembly and runs in-house training for public sector clients including the Home Office, the Department of Transport, the Biotechnology and Biological Sciences Research Council, the Health Foundation, and numerous local government and emergency services teams. He previously worked with Guardian Masterclasses on curating and delivering new course strands, including developing and teaching their B2B data visualisation courses. He oversaw the iPad edition launches of Wired, GQ, Vanity Fair and Vogue in the UK, and has worked with Condé Nast International as product owner on a bespoke digital asset management system for their 11 global markets. Testimonial “We’ve now worked with Alan for almost 3 years, and during that time he has continued to deliver the highest quality training for our clients and delegates. Alan’s passionate delivery style has continued to deliver innovative training solutions to over 1500 delegates across the public, private and voluntary sector. Each of our courses with him has always delivered exceptional feedback and satisfaction levels.” Joe Barlow | Head of Programme, Understanding ModernGov

During this 2 day course, you will develop a learning-based action plan to use in your workplace ensuring that you can put the learning into action.

During this 2 day course, you will develop a learning-based action plan to use in your workplace ensuring that you can put the learning into action.

During this 2 day course, you will develop a learning-based action plan to use in your workplace ensuring that you can put the learning into action.

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

Inspiring, interactive and unique 4-hour CPD certified training on Communication and Co-production with Parents/Carers

The course covers research design principles and all main quantitative evaluation methods: randomised experiments, instrumental variables, sharp and fuzzy regression discontinuity designs, regression methods, matching methods and longitudinal methods (before-after, difference-in-differences and synthetic controls).

The course covers research design principles and all main quantitative evaluation methods: randomised experiments, instrumental variables, sharp and fuzzy regression discontinuity designs, regression methods, matching methods and longitudinal methods (before-after, difference-in-differences and synthetic controls).