835 Teaching courses in Southend-on-Sea delivered Live Online

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El siguiente curso es una especialidad en el libro de Apocalipsis de la Biblia. Se trata sobre informar a los siervos de Dios de lo que va a suceder pronto para que estén preparados para la venida de Cristo.

Teaching4you is a tuition company that works to encourage and build confidence in students nationwide.

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

This is an online course sat at your own pace to introduce you to clinical coaching. As an Abbeydale training practice the cost of this course is including with the annual TP fee. During the course we will go into the concept of training a student, learning methods, tutorial techniques, safeguarding and how to use the Central Skills Log (CSL). The course is open for 2 months. Once completed we can then arrange access to the CSL for one of Abbeydale’s students.

Teaching4you is a tuition company that works to encourage and build confidence in students nationwide.

Canelo Publishing Masterclasses. Book your space to peek behind the scenes of a trade publisher. Learn about the different roles and departments, how books are made and published, and how publishers interact with readers and booksellers. Hear what it takes to ensure your book gets published and becomes a hit. Learn about the key things a publisher looks for when they consider submissions or publish books. Canelo will cover questions commonly asked, as well as answering your questions live. The winners of the I Am In Print Novel Award 2023 will also be announced!

Course Overview The Adobe InDesign course provides a comprehensive exploration of the software, focusing on its powerful tools for creating professional-level layouts and designs. Whether you're preparing marketing materials, publications, or digital assets, this course equips you with the essential skills to navigate the software with confidence. By the end of the course, you will have developed the proficiency to create visually appealing and highly functional documents suitable for various industries, helping to enhance your creative portfolio and advance your career in design and publishing. Course Description This course delves into the key features of Adobe InDesign, teaching learners how to use the software for creating professional publications. Topics covered include layout design, typography, image management, and mastering InDesign’s advanced tools. You will learn how to build multi-page documents, incorporate interactive elements, and refine text and image formatting for clear, aesthetically pleasing designs. Through a structured approach, learners will develop a solid foundation in creating both print and digital materials, honing skills in composition, design consistency, and brand alignment, enabling them to contribute to a wide range of design projects. Course Modules Module 01: Introduction to Adobe InDesign Overview of the interface Navigating tools and panels Setting up documents Basic design principles (See full curriculum) Module 02: Working with Text and Typography Text tool usage Typographic settings and styles Managing fonts and typography hierarchy Paragraph and character formatting (See full curriculum) Module 03: Image and Graphics Integration Inserting and editing images Working with vector graphics Image cropping and resizing Creating and applying effects (See full curriculum) Module 04: Master Pages and Templates Creating and using master pages Designing templates for consistency Applying templates across documents Effective page layout for multi-page documents (See full curriculum) Module 05: Exporting and Output Options Preparing files for print and digital formats Exporting PDFs and interactive documents Colour settings and file management (See full curriculum) Who is this course for? Individuals seeking to enhance their design skills. Professionals aiming to improve their proficiency in Adobe InDesign. Beginners with an interest in graphic design and publishing. Graphic designers, marketers, and creatives looking to broaden their software expertise. Career Path Graphic Designer Desktop Publisher Layout Artist Print Production Coordinator Marketing and Communications Specialist