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Duration 3 Days 18 CPD hours This course is intended for This course is geared for attendees with Intermediate IT skills who wish to learn Computer Vision with tensor flow 2 Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, with extensive practical exercises designed to reinforce fundamental skills, concepts and best practices taught throughout the course. Working in a hands-on learning environment, led by our Computer Vision expert instructor, students will learn about and explore how to Build, train, and serve your own deep neural networks with TensorFlow 2 and Keras Apply modern solutions to a wide range of applications such as object detection and video analysis Run your models on mobile devices and web pages and improve their performance. Create your own neural networks from scratch Classify images with modern architectures including Inception and ResNet Detect and segment objects in images with YOLO, Mask R-CNN, and U-Net Tackle problems faced when developing self-driving cars and facial emotion recognition systems Boost your application's performance with transfer learning, GANs, and domain adaptation Use recurrent neural networks (RNNs) for video analysis Optimize and deploy your networks on mobile devices and in the browser Computer vision solutions are becoming increasingly common, making their way into fields such as health, automobile, social media, and robotics. Hands-On Computervision with TensorFlow 2 is a hands-on course that thoroughly explores TensorFlow 2, the brandnew version of Google's open source framework for machine learning. You will understand how to benefit from using convolutional neural networks (CNNs) for visual tasks. This course begins with the fundamentals of computer vision and deep learning, teaching you how to build a neural network from scratch. You will discover the features that have made TensorFlow the most widely used AI library, along with its intuitive Keras interface. You'll then move on to building, training, and deploying CNNs efficiently. Complete with concrete code examples, the course demonstrates how to classify images with modern solutions, such as Inception and ResNet, and extract specific content using You Only Look Once (YOLO), Mask R-CNN, and U-Net. You will also build generative dversarial networks (GANs) and variational autoencoders (VAEs) to create and edit images, and long short-term memory networks (LSTMs) to analyze videos. In the process, you will acquire advanced insights into transfer learning, data augmentation, domain adaptation, and mobile and web deployment, among other key concepts Computer Vision and Neural Networks Computer Vision and Neural Networks Technical requirements Computer vision in the wild A brief history of computer vision Getting started with neural networks TensorFlow Basics and Training a Model TensorFlow Basics and Training a Model Technical requirements Getting started with TensorFlow 2 and Keras TensorFlow 2 and Keras in detail The TensorFlow ecosystem Modern Neural Networks Modern Neural Networks Technical requirements Discovering convolutional neural networks Refining the training process Influential Classification Tools Influential Classification Tools Technical requirements Understanding advanced CNN architectures Leveraging transfer learning Object Detection Models Object Detection Models Technical requirements Introducing object detection A fast object detection algorithm YOLO Faster R-CNN ? a powerful object detection model Enhancing and Segmenting Images Enhancing and Segmenting Images Technical requirements Transforming images with encoders-decoders Understanding semantic segmentation Training on Complex and Scarce Datasets Training on Complex and Scarce Datasets Technical requirements Efficient data serving How to deal with data scarcity Video and Recurrent Neural Networks Video and Recurrent Neural Networks Technical requirements Introducing RNNs Classifying videos Optimizing Models and Deploying on Mobile Devices Optimizing Models and Deploying on Mobile Devices Technical requirements Optimizing computational and disk footprints On-device machine learning Example app ? recognizing facial expressions

Duration 4 Days 24 CPD hours This course is intended for This course is geared for attendees with Intermediate IT skills who wish to learn Computer Vision with tensor flow 2 Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, with extensive practical exercises designed to reinforce fundamental skills, concepts and best practices taught throughout the course. Working in a hands-on learning environment, led by our Computer Vision expert instructor, students will learn about and explore how to Build, train, and serve your own deep neural networks with TensorFlow 2 and Keras Apply modern solutions to a wide range of applications such as object detection and video analysis Run your models on mobile devices and web pages and improve their performance. Create your own neural networks from scratch Classify images with modern architectures including Inception and ResNet Detect and segment objects in images with YOLO, Mask R-CNN, and U-Net Tackle problems faced when developing self-driving cars and facial emotion recognition systems Boost your application's performance with transfer learning, GANs, and domain adaptation Use recurrent neural networks (RNNs) for video analysis Optimize and deploy your networks on mobile devices and in the browser Computer vision solutions are becoming increasingly common, making their way into fields such as health, automobile, social media, and robotics. Hands-On Computervision with TensorFlow 2 is a hands-on course that thoroughly explores TensorFlow 2, the brand-new version of Google's open source framework for machine learning. You will understand how to benefit from using convolutional neural networks (CNNs) for visual tasks. This course begins with the fundamentals of computer vision and deep learning, teaching you how to build a neural network from scratch. You will discover the features that have made TensorFlow the most widely used AI library, along with its intuitive Keras interface. You'll then move on to building, training, and deploying CNNs efficiently. Complete with concrete code examples, the course demonstrates how to classify images with modern solutions, such as Inception and ResNet, and extract specific content using You Only Look Once (YOLO), Mask R-CNN, and U-Net. You will also build generative adversarial networks (GANs) and variational autoencoders (VAEs) to create and edit images, and long short-term memory networks (LSTMs) to analyze videos. In the process, you will acquire advanced insights into transfer learning, data augmentation, domain adaptation, and mobile and web deployment, among other key concepts. Computer Vision and Neural Networks Computer Vision and Neural Networks Technical requirements Computer vision in the wild A brief history of computer vision Getting started with neural networks TensorFlow Basics and Training a Model TensorFlow Basics and Training a Model Technical requirements Getting started with TensorFlow 2 and Keras TensorFlow 2 and Keras in detail The TensorFlow ecosystem Modern Neural Networks Modern Neural Networks Technical requirements Discovering convolutional neural networks Refining the training process Influential Classification Tools Influential Classification Tools Technical requirements Understanding advanced CNN architectures Leveraging transfer learning Object Detection Models Object Detection Models Technical requirements Introducing object detection A fast object detection algorithm ? YOLO Faster R-CNN ? a powerful object detection model Enhancing and Segmenting Images Enhancing and Segmenting Images Technical requirements Transforming images with encoders-decoders Understanding semantic segmentation Training on Complex and Scarce Datasets Training on Complex and Scarce Datasets Technical requirements Efficient data serving How to deal with data scarcity Video and Recurrent Neural Networks Video and Recurrent Neural Networks Technical requirements Introducing RNNs Classifying videos Optimizing Models and Deploying on Mobile Devices Optimizing Models and Deploying on Mobile Devices Technical requirements Optimizing computational and disk footprints On-device machine learning Example app ? recognizing facial expressions

Want to learn how to create eye-catching and engaging graphics for your business? Join our Using Canva workshop to find out how to utilise the online graphic design platform Canva to make everything from your company branding to social media posts and more! Event details: Time: 10am – 11:30am Location: Online (ZOOM) Cost: £25pp (£30pp from after April) In this course, we’ll cover everything from: How to sign up and get set up on the platform How to navigate Canva as a beginner Creating a brand kit for your business Creating a new graphic together for a campaign for a business Walkthrough of all the basic features of Canva Resizing designs to make posters and leaflets  As part of the live event of this workshop, we will also have a Questions and Answers session to finish this online workshop, where participants can ask specific questions about how to use Canva for their business. Meet the Host: Kerry Madge | Marketing Executive, Let's Do Marketing Kerry Madge is a dynamic Marketing Executive at Let's Do Marketing, bringing nearly six years of diverse experience collaborating with businesses of all sizes. Holding a BA in Marketing Management, Kerry excels in social media advertising, graphic design, and copywriting. Her passion lies in crafting creative solutions and developing comprehensive marketing strategies that empower small businesses to visualise and achieve their overarching goals. Privacy Notice By registering for this event, you agree to Let’s Do Business Group processing and managing your personal data in accordance with our Privacy Policy. Your data will only be used for the purposes of managing your event registration and any relevant communications.

FAA Level 3 Award In Supervising First Aid For Mental Health (RQF) Classroom (two day course), Virtual (6 x 2 ½ hour sessions) Gives learners knowledge of Mental Health First Aid and associated conditions This course is especially suitable for managers, supervisors and other staff that have the power to make changes in the workplace Course Contents: What is Mental Health? Why people develop mental health conditions What the role of a mental health first aider is Knowing how to provide advice and practical support Knowing how to recognise and manage stress Understand the impact of substance abuse on mental health Understand the first aid action plan for mental health and be able to put it in place Know how to implement a positive mental health culture in the workplace Recognising a range of mental health conditions: Depression Anxiety Psychosis Eating disorders Suicide Self-harm PTSD Personality disorders Bipolar disorder Schizophrenia Benefits of this course: 37% of all work-related ill-health is due to mental health problems Problems with mental health cover 45% of all working days lost A whopping 12.8 million working days, or 49, 042 years, were lost due to mental health problems in 2018/19 602,000 workers suffered from work-related stress, depression or anxiety in 2018/19 One in four people will have a mental health problem at some point during their lives Whether work is causing or aggravating mental health problems, employers have a legal responsibility towards their employees Work-related mental health issues must to be assessed to measure the levels of risk to staff Where a risk is identified, steps must be taken to remove it or reduce it as far as reasonably practicable This two day r employees' mental health and wellbeing Accredited, Ofqual regulated qualification Our Mental Health First Aid Courses are nationally recognised, Ofqual regulated qualifications accredited by First Aid Awards Ltd in association with NUCO Training. This means that you can be rest assured that your Mental Health First Aid Certificates fulfill the upcoming legal requirements and are a very good way to make sure you and your employees have a supporting workplace to deal with staff's mental health conditions. The Ofqual Register number for this course is 603/3770/9

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The qualification is aimed at learners already working or preparing to work in industry that is identified within the company's risk assessment of First Aid. The qualification has a recommended course duration of 2 days; however the course duration may be increased to meet additional learning needs if required but not reduced.

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This course covers road-tow equipment - from legal checks, tyres, lighting through to brake checks, adjustment and repairs. Ideal for tool hire, plant hire. CPA Members HAE Members and IPAF Members for their Fitters, mechanics, technicians, Check and Test, Test and Run, PDI Techs, not forgetting Charities or other organisations who run maintain or sell trailer mounted items nd those that sell, deal in or refurbish equipment.

The Mechanics of Mediumship. A beginners guide to everything you need to know. How to become a professional psychic medium. Able to give short, accurate, evidential messages. This course runs over 5 weeks and during our time together we will explore five easy to follow parts. 1: What mediumship is and the different types, including your role as a professional medium and the differences between working in the psychic modality and when you are connected to spirit. 2: Activating and building your power within, and the difference between meditation, and attunement both to the spirit world and using your psychic modality. 3: The six different senses available to you, which are your strongest and whether you are perceiving them objectively or subjectively. 4: What is and what is not evidence in mediumship, understanding the different types of evidence available and defining practical and emotional evidence. 5: Surrendering to spirit, building confidence to receive specific unique information, and understanding the reasons why you receive a no response. Guidance on making positive, strong, statements filling your sitter with confidence, building a truly extraordinary professional reading.