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
FAA Level 1 Award In Awareness Of First Aid For Mental Health (RQF) Classroom (4.5 hour course), Virtual (2 x 2 ½ hour sessions) Gives learners a good awareness of Mental Health First Aid Gives learners the skills to start that difficult conversation 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 Recognising a range of mental health conditions: Depression Anxiety Psychosis Eating disorders Suicide Self-harm 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 half day course gives people a good awareness of mental health in the workplace For a more complete introduction, see our full day First Aid for Mental Health or two day Supervising First Aid for Mental Health courses Accredited, Ofqual regulated qualification This Awareness of Mental Health First Aid Course is a nationally recognised, Ofqual regulated qualification accredited by First Aid Awards. This means that you can be rest assured that your Mental Health First Aid Certificates fulfil 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 603/3768/0
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
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.
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 1.5 Days 9 CPD hours This course is intended for This course is intended for individuals who want to gain basic knowledge communicating, etiquette, professionalism and time management for the office environment. Overview Upon successful completion of this course, students will be able to communicate, be professional and manage their time effectively in a business environment. In this course, students will learn how to communicate, act and manage time effective in a business environment. Getting Started Icebreaker Housekeeping Items The Parking Lot Workshop Objectives The Big Picture What is Communication? How Do We Communicate? Other Factors in Communication Understanding Communication Barriers An Overview of Common Barriers Language Barriers Cultural Barriers Differences in Time and Place Paraverbal Communication Skills The Power of Pitch The Truth about Tone The Strength of Speed Non-Verbal Communication Understanding the Mehrabian Study All About Body Language Interpreting Gestures Speaking like a Star S = Situation T = Task A = Action R = Result Summary Listening Skills Seven Ways to Listen Better Today Understanding Active Listening Sending Good Signals to Others Asking Good Questions Open Questions Closed Questions Probing Questions Appreciative Inquiry The Purpose of AI The Four Stages Examples and Case Studies Mastering the Art of Conversation Level One: Discussing General Topics Level Two: Sharing Ideas and Perspectives Level Three: Sharing Personal Experiences Our Top Networking Tips Advanced Communication Skills Understanding Precipitating Factors Establishing Common Ground Using ?I? Messages Wrapping Up Words from the Wise Review of Parking Lot Lessons Learned Completion of Action Plans and Evaluations Principles of Professional Behavior Always be Your Best Meeting and Greeting Sending Social Invitations to Business Associates Interview Etiquette Interviewing Before the Interview In the Waiting Room During the Interview After the Interview Job Fair Interviews Planning & Attending Business Meetings Office Meetings Meal Meetings Electronic Etiquette Voicemail Cell Phones Email Multiculture Etiquette Defining the Challenge Five Steps to Dealing with Diversity Guidelines for Managing Diverse Relationships Time Management Concepts Benefits of better time utilization Who controls your schedule? Your Job: What You Are Responsible for Accomplishing? Your job responsibilities Setting objectives Setting priorities How to Use Your Time Gathering data-the time log Analyzing the data Delegation: Working Through Others Why some people don't delegate Levels of delegation How to delegate Benefits of delegation Getting started Planning: Keys to Achievement Planning: Keys to Achievement Coping with Common Time Wasters Coping with self-generated time wasters Coping with environmental time wasters Personal Needs that Get in the Way of Effective Time Utilization Needs profile analysis Self-assessment questionnaire Applying needs assessment results Planning for Improvement Six tips for effective time management Planning for improved time utilization Follow-Up: Staying on Track Time savings progress report Time savings progress chart Time management progress survey Additional course details: Nexus Humans Business Soft Skills 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 Business Soft Skills 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.
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.
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.