1729 AI courses in Cardiff delivered Live Online

Course Overview The DeepSeek Masterclass: A Complete DeepSeek Zero to Hero! is designed to provide learners with a comprehensive understanding of DeepSeek AI from the ground up. Whether you are new to artificial intelligence or seeking to deepen your expertise, this course offers a structured journey through DeepSeek's functionalities and real-world applications. Learners will discover how to navigate DeepSeek for software development, business innovation, and educational advancement. Through this masterclass, individuals will build a strong theoretical foundation, explore diverse use cases, and emerge with the confidence to implement DeepSeek-driven strategies in a range of professional environments. By the end of the programme, learners will have developed the knowledge and insights necessary to use DeepSeek as a transformative tool across multiple disciplines. Course Description This in-depth course covers a wide range of essential topics, including the foundations of artificial intelligence, DeepSeek system setup, and its applications across various sectors such as business, education, and software development. Learners will explore how DeepSeek can be leveraged to create smart solutions for students, empower business professionals, and support teaching practices. The masterclass delivers an immersive learning experience that blends conceptual knowledge with strategic application insights. Participants will build expertise in utilising DeepSeek to enhance efficiency, support innovation, and foster professional growth. Whether learners are looking to enter the AI space or to future-proof their careers, this course equips them with the essential skills and understanding to confidently engage with DeepSeek technologies in a competitive landscape. Course Modules Module 01: Getting Started Module 02: Foundations of Artificial Intelligence (AI) Module 03: Setting up DeepSeek AI for Beginners Module 04: DeepSeek for Software Developers Module 05: DeepSeek for Business Professionals Module 06: DeepSeek Smart Solutions for Students Module 07: The Power of DeepSeek Module 08: DeepSeek for Teaching Professionals (See full curriculum) Who is this course for? Individuals seeking to master DeepSeek AI from basic to advanced levels. Professionals aiming to integrate DeepSeek solutions into their organisations. Beginners with an interest in artificial intelligence, software development, or educational technology. Educators and trainers wishing to incorporate AI-based strategies into teaching. Career Path AI Solutions Specialist Software Developer (AI Focus) Business Innovation Consultant Educational Technology Specialist Data Analysis Support Roles AI Application Support Officer Digital Transformation Assistant

This is a quickstart Adobe Express Training course held online in Janury 2025. Ideal for business owners or freelancers looking to get to grips with social media design and designing for social media marketing.

Thursday 3 July,10am - 12.30pm    Are you interested in developing programmes and exhibits with LGBTQ+ content for children and families?    About this training    During this training session, we will address the challenges museum staff and volunteers face when creating LGBTQ+ content for children and families. Alongside this we will discuss strategies for advocating for this content and explore resources for planning and implementation.    This webinar will be led by Margaret Middleton, a freelance exhibit designer and museum consultant based in Manchester. Their background is in children's museums and they have written and consulted widely on creating LGBTQ+ museum content for families, especially those with children aged 10 and under.    Margaret will be joined by Dylan Saul, Family Programmes Facilitator and Moa Strand, Families and Young People Programmes Manager at Royal Museums Greenwich and Daniel Jessop, Learning and Community Engagement Officer at Novium Museum, who will talk about their LGBTQ+ work for children and families.     The session will help you to:  Understand the importance of this work, Think critically about the challenges you may face undertaking this work, Develop ways to advocate for this work, Gain inspiration from case studies to take your own work forward.   Take a look at the full schedule.    This training event will be delivered virtually on Zoom over one half-day session (two hours and 30 minutes with a short break).     Who should attend?  This training is aimed at staff and volunteers who work in museums, art galleries and heritage sites and are interested in developing programmes and exhibits with LGBTQ+ content for children and families.   

This one day masterclass is designed to provide a practical application of the content that is covered within The DEI Playbook and is aimed at anyone tasked with launching and implementing diversity and inclusion within their organisation.

Duration 2 Days 12 CPD hours This course is intended for This course is intended for Business Leaders, including managers/supervisors in the following roles: Developer Architect Video Operator Overview In this course, you will learn to: Articulate the essential terms and concepts fundamental to video compression and distribution Describe the four fundamental stages of video streaming workflows: ingest, process, store and deliver Explain the importance of security in the AWS Cloud and how it is applied in video streaming workflows Analyze video streaming workflow diagrams using AWS services, based on simple to complex use cases Describe some of the key variables that influence workflow decisions Recognize how other AWS services for compliance, storage, and compute, interact with AWS Media Services in video streaming workflows and the functions they perform Describe strategies to test or prototype workflows to mitigate risk and cost impacts and optimize video streaming workflows Use the AWS Management Console to build and run simple video streaming workflows for live and video-on-demand content Recognize the automation and data analytics available for Media Services when used with AWS AI and explore media-specific use cases for these services Identify the next steps in exploring migration to the cloud for one or more Media Services This course covers the media and cloud fundamentals that will empower you to develop a cloud migration strategy for media workflows in support of business goals. The course covers important concepts related to video processing and delivery, the variables that can impact migration decisions, and real-world examples of hybrid and cloud use cases for AWS Media Services. It also introduces security, artificial intelligence, and analytics concepts to help you consider how AWS Media Services fit into your overall cloud strategy. Module 1: Important video concepts Video Metrics Video Compression Video Distribution Major Protocols Used in Video Streaming Module 2: Anatomy of streaming workflows Ingest Process Store Deliver Module 3: Using AWS services in media workflows video-on-demand (VOD) Introduction to AWS Media Services Security Variables Impacting Workflow Design VOD Simple Use Cases VOD Advanced Use Cases Lab 1: Build and run a simple video streaming workflow for VOD content Module 4: Using AWS services in media workflows live streaming Challenges of Live Streaming Live Streaming Simple Use Cases Live Streaming Advanced Use Cases Lab 2: Build and run a simple video streaming workflow for live content Module 5: Optimizing Workflows Cost Considerations Mitigating Risk Monitoring and Automation Exploring Migration Options Additional course details: Nexus Humans AWS Media Essentials for IT Business Decision Makers 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 AWS Media Essentials for IT Business Decision Makers 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.

ChatGPT Masterclass: A Complete ChatGPT Zero to Hero! Course Overview The ChatGPT Masterclass: A Complete ChatGPT Zero to Hero! course is designed to guide learners from basic understanding to advanced proficiency in using ChatGPT. This course covers a wide range of topics, from the fundamentals of ChatGPT to its integration for business scaling and its applications in specific industries like Excel professionals and students. By the end of the course, learners will have a comprehensive understanding of ChatGPT’s capabilities, how to leverage its potential for various tasks, and how to improve productivity and creativity using this powerful tool. Whether you are looking to enhance your business, excel in academic pursuits, or integrate AI into your work, this course provides the knowledge and skills necessary to succeed. Course Description This course offers an in-depth exploration of ChatGPT, covering its fundamental features and uses across different sectors. Learners will be introduced to ChatGPT’s functionalities, followed by more specialised modules, including its applications for developers, students, and professionals working with Excel. Participants will gain valuable insights into how ChatGPT can be used to automate tasks, enhance business operations, and create innovative content. They will also explore the integration of Dall-E 2 for generating graphic art and the best tools and extensions to improve ChatGPT's functionality. The course is structured to ensure learners gain a clear understanding of how to effectively use ChatGPT for various personal and professional goals. ChatGPT Masterclass: A Complete ChatGPT Zero to Hero! Curriculum Module 01: Getting Started Module 02: ChatGPT – Basic Module 03: ChatGPT for Developers Module 04: Build, and Scale your Business Using ChatGPT Module 05: ChatGPT for Students Module 06: The Power of ChatGPT Module 07: ChatGPT for Excel professionals Module 08: Generate Incredible Graphic Art with Dall-E 2 Module 09: The Best Tools and Extensions using ChatGPT (See full curriculum) Who is this course for? Individuals seeking to improve productivity through AI. Professionals aiming to leverage ChatGPT for business growth. Beginners with an interest in learning AI technologies. Developers looking to integrate ChatGPT into applications. Students seeking to optimise learning and research tasks. Career Path AI Integration Specialist Business Automation Expert Developer specialising in AI tools Digital Content Creator Data Analyst using AI tools Academic Support Professional Graphic Designer using AI for art generation

MECC for Mental Health This course will provide you information about how to use the Making Every Contact Count (MECC) approach, talking about mental health and where to direct people to within those conversations Aims of the Course On completion you will understand: How mental health and wellbeing affect people in every day settings. How to feel confident in discussing mental health and wellbeing. How to start and have a mental health and wellbeing conversation. Mental health in the workplace. Available mental health and wellbeing support and resources. Who is the course aimed at ? The course is not only aimed at people supporting people with their mental health and wellbeing, but also those whose roles might not traditionally have any mental health training but have the opportunity to discuss mental health and wellbeing. This could include settings such as libraries, gyms, charity support services, hairdressers, and other public facing settings. The course could also be used in the induction of new staff and volunteers across a variety of workplaces.

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 module aims to develop knowledge and understanding of customs procedures associated with international trade. The module includes trade agreements, tariffs and taxes, immigration, intellectual property rights, clearance procedures, transport regulations, sanitary and Phyto-sanitary measures, customs valuation, preference systems and anti-dumping measures.