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EMDR Refresher Workshop with Simon Proudlock and Ines Santos – EMDR Europe Accredited Trainers The aim of this workshop is to sharpen your skills, refresh your confidence & stay true to the model. Over time, even skilled practitioners can experience therapy drift. This workshop offers a structured and supportive space to revisit the standard protocol and re-ignite your clinical clarity. We'll explore common uncertainties (e.g. "Is BLS fast or slow in the installation phase?"—Answer: fast!), deepen understanding of each protocol phase, and reinforce model fidelity. Who is it for? ✔ EMDR therapists looking to refresh their knowledge and skills ✔ Practitioners who've had limited opportunities to use EMDR and want to build confidence ✔ Therapists working towards EMDR Accreditation (Practitioner or Consultant) seeking to strengthen their adherence to the model Content: Re-cap of the 8-phase protocol and rationale for each stage Updates on current research and developments in EMDR Refresher on the AIP model and its role in case formulation Therapeutic/Cognitive Interweaves Working with recent events Flashforward and Absorption Techniques Video examples from real clinical sessions Ample opportunity for supervised practice and feedback Key Learning Outcomes: To increase confidence in using EMDR with a range of clients To explore current blocks in using EMDR To increase confidence in using Cognitive Interweaves To learn additional techniques that may have not been covered in initial training For those who want the opportunity to practice, as an add-on to the workshop, we will be offering a 3-hour supervised practicum on Monday 8th December at 9am bookable at time of checkout as an add-on. There is also the option of free access to Practice EMDR, an innovative ‘Flight Simulator’ to practice with an AI avatar. Simon Proudlock is a Consultant Psychologist and Associate Fellow of the British Psychological Society working for the NHS and in private practice. He has spent the majority of his career working with complex clients. In 2018 he achieved the award for Innovative Practice by the Division of Counselling Psychology for his research in EMDR with people who are suicidal. He is author of 'The Solution Focused Way: Incorporating Solution Focused Therapy Tools and Techniques into Your Everyday Work'. Ines Santos is a Clinical Psychologist, specialist in trauma and complex trauma, with over 20 years of experience in the NHS, including working at the Traumatic Stress Service, Maudsley. Ines developed the EMDR Case Formulation Tool and has delivered several workshops on EMDR case formulation in treatment planning and target selection; as well as workshops on EMDR Advanced Techniques and EMDR Refresher workshops. Simon and Ines are EMDR Europe Accredited Trainers & Consultants. The workshop fee includes handouts, CPD certificates and access to the recording of the webinar for 45 days after the event for those who have attended in person only. EMDR UK Association - 6 CPD points PENDING

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

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Learn to build chatbots for various platforms such as Facebook, Slack, Skype, Kik, Telegram and others with the Chatbots for Multiple Platforms - Without Coding course. A chatbot is a computer program or an artificial intelligence which is designed to simulate a conversation with human users, especially over the Internet via auditory or textual methods. In the course, you will learn to create chatbots for various platforms without coding. The course shows you the techniques of developing sophisticated chatbots that use button and Ai to ensure great customer experience. You will learn to build a chatbot in Gupshup.io, Motion.ai, and more. The course helps you to develop the first bot. Upon completion, you will be able to create chatbots that can able to perform various operations. What Will I Learn? By the end of the course you will be able to build an iBeacon enabled mobile app ready to be submitted to the app stores (Apple and Google Play) You will understand what an iBeacon is and what are some of the potential uses. You will understand what programs are needed to build beacon apps and where to download them (for free). You will understand the different types of beacons, what are the costs involved, what services are provided by the various beacon makers. You will know how to build an app for testing and giving to your clients for testing. Requirements You need to have a MAC computer to build the apps - currently PC is not supported. It is also possible to do this on a Windows machine if you install a Virtual machine and run the MAC OS in a window on your PC. Take a look at this for an overview: https://blog.udemy.com/xcode-on-windows/ For testing iBeacon functionality you will need 2 things. 1) a device to act as a beacon, and 2) an i Device or an Andoid Device (details in the course). A desire to learn! This is not difficult, it only takes following instructions and havign a desire to learn. Who is the target audience? Web and Mobile designers, marketing people, and business ownvers who want to learn how to leverage the next level of mobile interactions by incorporating iBeacons. No programming background needed - this is really a course for anyone - you really do not need to have any coding background. Marketing and retial people are also encouraged to take this course to understand the potential for greater customer interactions made possible with iBeacons. Mobile phone app makers who want to learn how to incorporate iBeacons into existing apps the easy and fast way. Introduction to Chatbots 1. Introduction 00:03:00 2. Chatbot Examples 00:06:00 Building a Chatbot in Gupshup.io 2. Introduction to Gupshup 00:02:00 3. Gupshup Travel Bot Part 1 00:11:00 4. Gupshup Improving the User Experience 00:02:00 5. Gupshup Order an Uber 00:02:00 7. Gupshup Helsinki Weather 00:04:00 8. Gupshup Publishing Your Bot 00:02:00 Gobot Easy and Powerful Ready Made Chatbot Services 1. Gobot Introduction 00:01:00 3. GoBot Site Example 00:02:00 4. Gobot Parts of the System 00:01:00 5. Gobot Make a bot Part 1 00:08:00 6. Gobot Make a bot Part 2 00:03:00 7. Gobot Publishing your Bot 00:08:00 A Facebook Messenger Bot 1. Introducing Chatfuel 00:02:00 2. Understanding A Chatfuel Bot - Test Bot 00:05:00 3. Building Our Own Facebook Messenger Bot - A Retail Example part 1 00:02:00 4. Catfuel and Images - Getting them right 00:06:00 5. Chatfuel Product Gallery with More Information 00:09:00 6. Chatfuel - Plugins - Adding an RSS feed with Subscription 00:07:00 7. Chatfuel - Plugins - YouTube Integration 00:07:00 8. Chatfuel - Collecting Uder Input via Email 00:06:00 9. Chatfuel - Advanced Features 00:09:00 10. Chatfuel - Work Around for Button Linking Problem 00:02:00 11. Chatfuel - Add a Site Search - Bing or Google Search 00:07:00 12. Chatfuel - Publish Your Bot - Two Options 00:03:00 UPDATE - MiniApp Chatbot Building System 1. Introduction to MiniApp 00:02:00 2. Connecting a MiniApps Bot to the Microsoft Bot Framework 00:10:00 3. MiniApps Creating the Bot Interactions 00:04:00 4. MiniApps Connecting your bot to Skype 00:02:00 5. MiniApps Simple now but other options are possible 00:01:00 6. MiniApps Conslusion 00:02:00 Building a Chatbot in Motion.ai 2. Looking at the Motion.ai Interface 00:02:00 3. Motion.ai Interface Part 2 00:02:00 Building Our First Bot - A travel bot 1. Part 1 - Setting up the Travel Bot 00:01:00 2. Part 2 - Looking at The Connections 00:02:00 3. Part 3 - Adding Buttons via HTML and Cards 00:07:00 4. Part 4 - Adding Other Content with Widgets - Weather Example 00:03:00 5. Part 5 - Connecting Your Bot to Another Bot - Uber Example 00:03:00 6. Part 6 - Creating Multiple Cards - Travel Sights Bot 00:10:00 7. Part 7 - Clean-up - Global Settings and Help 00:03:00 Entertainment bot Example - The Bender Bot 1. Bender Bot Part 1 - Looking at how the bot works 00:04:00 2. Bender Bot Part 2 - Advanced - Adding a new interaction 00:06:00 3. Bender Bot Part 3 - Final connnections and things to think about with Motion.ai 00:09:00 Thank You 1. Thank you and contacts 00:01:00

Aims of the Course The module supports anyone who is not a physical activity specialist by supplying high quality and evidence based physical activity training that develops knowledge, skills and confidence to integrate relevant physical activity messages and interventions into everyday conversations. On completion you will have awareness of: The MECC approach and how this can be applied in your setting. What is meant by physical activity (including awareness of the latest Chief Medical Officer’s guidelines). How to deliver healthy lifestyle messages linked to physical activity, to encourage people to change their behaviour. Where suitable resources for signposting can be found. Who is the course aimed at? The course is aimed at anybody interested in looking to support physical activity conversations in the workplace or community. It is particularly useful for workplace health champions, and those who are responsible for workplace health and wellbeing strategies. No previous knowledge is required in order to obtain the content of this course. How long is the course? The course is delivered over a 2.5 hour online session. Though this course is offered to you fully funded, please make every effort to attend once you have enrolled, or make us aware so that someone else may benefit. Thank you!

Duration 3 Days 18 CPD hours This course is intended for This course is geared for Python experienced developers, analysts or others who are intending to learn the tools and techniques required in building various kinds of powerful recommendation systems (collaborative, knowledge and content based) and deploying them to the web. Overview This skills-focused combines engaging lecture, demos, group activities and discussions with machine-based student labs and exercises.. Our engaging instructors and mentors are highly-experienced practitioners who bring years of current, modern 'on-the-job' modern applied datascience, AI and machine learning experience into every classroom and hands-on project. Working in a hands-on lab environment led by our expert instructor, attendees will Understand the different kinds of recommender systems Master data-wrangling techniques using the pandas library Building an IMDB Top 250 Clone Build a content-based engine to recommend movies based on real movie metadata Employ data-mining techniques used in building recommenders Build industry-standard collaborative filters using powerful algorithms Building Hybrid Recommenders that incorporate content based and collaborative filtering Recommendation systems are at the heart of almost every internet business today; from Facebook to Net?ix to Amazon. Providing good recommendations, whether its friends, movies, or groceries, goes a long way in defining user experience and enticing your customers to use your platform.This course shows you how to do just that. You will learn about the different kinds of recommenders used in the industry and see how to build them from scratch using Python. No need to wade through tons of machine learning theory?you will get started with building and learning about recommenders as quickly as possible. In this course, you will build an IMDB Top 250 clone, a content-based engine that works on movie metadata. You will also use collaborative filters to make use of customer behavior data, and a Hybrid Recommender that incorporates content based and collaborative filtering techniques. Students will learn to build industry-standard recommender systems, leveraging basic Python syntax skills. This is an applied course, so machine learning theory is only used to highlight how to build recommenders in this course. Getting Started with Recommender Systems Technical requirements What is a recommender system? Types of recommender systems Manipulating Data with the Pandas Library Technical requirements Setting up the environment The Pandas library The Pandas DataFrame The Pandas Series Building an IMDB Top 250 Clone with Pandas Technical requirements The simple recommender The knowledge-based recommender Building Content-Based Recommenders Technical requirements Exporting the clean DataFrame Document vectors The cosine similarity score Plot description-based recommender Metadata-based recommender Suggestions for improvements Getting Started with Data Mining Techniques Problem statement Similarity measures Clustering Dimensionality reduction Supervised learning Evaluation metrics Building Collaborative Filters Technical requirements The framework User-based collaborative filtering Item-based collaborative filtering Model-based approaches Hybrid Recommenders Technical requirements Introduction Case study and final project ? Building a hybrid model Additional course details: Nexus Humans Building Recommendation Systems with Python (TTAI2360) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Building Recommendation Systems with Python (TTAI2360) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

About Course Master the fundamental building block of the web and learn to create beautiful and functional websites with HTML5. In this comprehensive course, you will learn: The basics of HTML syntax, including elements, attributes, and tags. How to structure your web pages using HTML5 semantic elements. How to add images, videos, and other multimedia content to your websites. How to create interactive web pages using forms and buttons. How to style your websites using CSS. This course is perfect for beginners with no prior experience in HTML. However, if you have some programming experience, you will be able to learn the material more quickly. You will learn from an experienced web developer who will teach you the concepts and skills you need to succeed. By the end of this course, you will be able to: Create and structure web pages using HTML5. Add multimedia content and interactive elements to your websites. Style your websites using CSS. Build a portfolio of real-world websites Throughout the course, you will work on a variety of hands-on projects to build your skills and create a portfolio of real-world websites. Join a supportive community of learners You will have access to a dedicated student forum where you can ask questions and get help from the instructor and other students. Enroll today and start your journey to becoming a web developer! Bonus: Get access to the instructor's personal collection of HTML5 resources. Why learn HTML5? HTML5 is the latest version of HTML, and it is the most widely used markup language in the world. It is used to create the structure and content of web pages. HTML5 is a powerful tool that can be used to create a variety of websites, from simple static pages to complex dynamic applications. Here are some of the benefits of learning HTML5: HTML5 is easy to learn, even for beginners. HTML5 is a versatile language that can be used to create a variety of websites. HTML5 is in high demand, and there are many job opportunities for HTML5 developers. HTML5 is a valuable skill to have, even if you are not planning to become a web developer. So what are you waiting for? Enroll in this course today and start your journey to becoming a web developer! What Will You Learn? Become a modern and confident HTML developer, no prior knowledge needed! Learn to quickly apply CHatGPT AI skills for your website development Design and build a stunning real-world project for your portfolio from scratch A web design framework with easy-to-use rules and guidelines to design eye-catching websites How to make websites work on every possible mobile device (responsive design) You will learn quickly prompt engineering skills to make real-world websites Learn to Publish your website on production servers using FTP app Course Content Getting Started Introduction to Getting Started Course Curriculum How to Get Pre - Requisites Getting Started on Windows, Linux or Mac How to Ask Great Questions FAQ's HTML Setting Up Local Environment Introduction to HTML Choosing Code Editor Installing Code Editor (Sublime Text) Overview of a Webpage Structure of a Full HTML Webpage First Hello World Webpage Summary HTML Basic Introduction Heading Tags Paragraph Formatting Text List Items Unordered List Items Ordered Classes IDs Comments Summary HTML Intermediate Introduction Images Forms Form Actions Br Tag Marquee Text Area Tables Links Navbar - Menu HTML Entities Div Tag Google Maps Summary HTML Advanced Introduction HTML5 Audio HTML5 Video Progress Bar Drag and Drop Canvas Iframes Input Types Input Attributes YouTube Video Linking Creating Responsive Page Summary HTML Expert Introduction Registration Form Login Form About Us Form Contact Us Form Footer Form Integrate All Together Coding Exercise Solution for Coding Exercise Summary Publish Your Website Live Introduction Installing Free FTP Solution (FileZilla) Setting Up FTP (File Transfer Protocol) Publish Website to Hosting Server Summary HTML Website Project Introduction Challenge - HTML 5 Clock Face with Numbers Project Overview Conclusion on Project Summary A course by Sekhar Metla IT Industry Expert RequirementsNo coding or design experience necessary for this courseAny computer works - Windows, Linux or macOSYou don't need to buy any software - we will use the best free code editor in the world