15 AI (Artificial Intelligence) courses delivered Live Online

Bitesize Masterclass on AI - facilitated by Fiona Young, Leading Expert and Trainer.    Are you a total beginner to AI? Or maybe you've dabbled but found it all overwhelming...or underwhelming?  Then this bitesize masterclass on AI is for you!    We'll be covering AI fundamentals, what AI means for exec support roles, and practically how to use AI chatbots (like ChatGPT and Copilot) to shortcut admin drudgery.    You’ll come away from this session with the confidence and skills to start using AI in your workflow right away, making you more efficient and giving you time back to do more of the human work you love.    Note that this is NOT a passive webinar — we'll have demos, discussions and breakouts. You'll get a chance to practice using AI chatbots in the room for real world projects with other forward-thinking assistants like you.  Here's a detailed breakdown of session content: AI fundamentals  •    Defining AI, gen AI and other need to know terms  •    Key AI risks to be aware of  •    Exciting tools for assistants right now How AI will change the assistant role  •    Explore our feelings about AI right now  •    Some predictions on what AI means for the future of exec support  •    What you can do to win in the age of AI A practical guide to using ChatGPT and LLMs at work  •    How to use AI chatbots in your workflow  •    How to craft great prompts to optimise outputs  •    A chance to practice & workshop prompting in the room   Fiona Young is founder of Carve, a series of live digital courses for executive assistants to learn AI, create capacity and develop into a strategic assistant — carving out their career growth in the process. Before launching Carve, Fiona spent five years leading learning programs at Hive Learning, the b2b peer learning app. She previously ran Learning & Development for Blenheim Chalcot, one of the world’s most successful venture builders, overseeing group learning strategy and programs for 3,000 people across 25 ventures.  Fiona started her career as an executive assistant in entrepreneurial businesses. 

This course shows you how to apply various approaches and algorithms to solve business problems through AI and ML, follow a methodical workflow to develop sound solutions, use open-source, off-the-shelf tools to develop, test, and deploy those solutions, and ensure that they protect the privacy of users. This course includes hands-on activities for each topic area.

This half-day course is for anyone who wants to learn how to use AI and specifically ChatGPT to improve their marketing and social media.

Mastery of ChatGPT, Chatbots and AI for Chiropractors, Osteopaths, Physiotherapists. Leverage AI to enhance patient and clinic interaction. -------------------------------------------------------------------------------- AGENDA 08:45 - 09:00 Registration 09:00 - 09:45 ChatGPT and AI basics 09:45 - 11:00 Prompt Engineering with ChatGPT 11:00 - 11:15 Break - Morning Coffee 11:15 - 13:00 ChatGPT in Healthcare 13:00 - 13:30 Break - Lunch 13:30 - 14:30 AI & ChatGPT for the Clinic 14:30 - 15:15 AI for Patient Engagement 15:15 - 15:30 Break - Afternoon Tea 15:30 - 16:15 Streamlining Clinic Operations 16:15 - 17:00 Best Practices & Strategy -------------------------------------------------------------------------------- 🌟 Introducing: A Revolution in Healthcare Operations! 🌟 Are you a healthcare professional looking to stay ahead of the curve? Dive into the future with Duforest AI's groundbreaking course, meticulously designed just for you! 🔹 Why this course? In a fast-paced healthcare environment, staying updated with the latest technological advancements is not a luxury; it's a necessity. Our course doesn't just introduce you to the realm of prompt engineering and virtual assistants – it shows you how to weave them seamlessly into your practice. Whether you're a chiropractor, osteopath, physiotherapist, or acupuncturist imagine enhancing patient interactions and propelling your practice to unprecedented efficiency. 🔸 Course Highlights: ✓ CPD-accredited for utmost credibility ✓ Tailored approach for chiropractors, osteopaths, physiotherapists, and acupuncturists ✓ Master the art of integrating ChatGPT and other AI tools ✓ Explore ethical considerations, ensuring patient trust and safety ✓ Boost operations with actionable communication strategies 🔹 Join the Future of Healthcare The age of AI in healthcare isn't looming; it's here. This course bridges the gap between the current and the new, ushering in an epoch of healthcare brilliance. It's time you brought the cutting-edge of AI right to your clinic's doorstep. Don't be left in the past. Embrace the future with Duforest AI. Sign up today and stride confidently into a smarter healthcare horizon! Register now for EARLY BIRD pricing and to ensure your participation! -------------------------------------------------------------------------------- TAGS * Online Events * Things To Do Online * Online Classes * Online Science & Tech Classes * #osteopathy * #chatbot * #ostéopath * #chatgpt * #chatgpt_training * #osteopathy_seminar

Why Learn Sketchup and Stable Diffusion Rendering Course? Course Link [https://www.londondesigntrainingcourse.co.uk/product-page/sketchup-and-stable-diffusion-rendering-course] SketchUp and Stable Diffusion Rendering Course. An AI image creation course designed to explore AI image creation techniques and master the use of advanced AI technology. You'll learn Ai 3D modeling, advanced rendering, and lighting techniques. Duration: 16 hrs. Method: 1-on-1 Online Over Zoom is also available. Schedule: Tailor your own schedule by pre-booking a convenient hour of your choice, available from Mon to Sat between 9 am and 7 pm. The Sketchup and Stable Diffusion Rendering Course equips students with comprehensive skills for visually stunning Ai (Artificial intelligence) 3D models and renderings. Master Sketchup's user-friendly interface, advanced rendering techniques, and stable diffusion rendering. Hands-on exercises and real-world projects enhance learning. Ideal for architecture, interior design, product development, and visualization careers. The Sketchup and Stable Diffusion Rendering Course equips students with comprehensive skills for visually stunning Ai (Artificial intelligence) 3D models and renderings. Master Sketchup's user-friendly interface, advanced rendering techniques, and stable diffusion rendering. Hands-on exercises and real-world projects enhance learning. Ideal for architecture, interior design, product development, and visualization careers. Sketchup and Stable Diffusion Rendering Course (16 hours) Module 1: Introduction to Sketchup (2 hours) * Overview of Sketchup software and interface navigation * Basic drawing tools and geometry creation techniques Module 2: Texturing and Materials (2 hours) * Applying textures and customizing materials * Exploring texture mapping and material libraries Module 3: Lighting and Shadows (2 hours) * Understanding lighting principles and light placement * Creating realistic shadows and reflections Module 4: Advanced Modeling Techniques (3 hours) * Creating complex shapes and utilizing advanced tools * Working with groups, components, and modifiers Module 5: Stable Diffusion Rendering (2 hours) * Introduction to stable diffusion rendering * Configuring rendering settings for optimal results Module 6: Scene Composition and Camera Setup (2 hours) * Exploring composition principles and camera perspectives * Managing scenes and creating walkthrough animations Module 7: Rendering Optimization (2 hours) * Optimizing models for faster rendering * Using render passes and post-processing techniques Module 8: Project Work and Portfolio Development (1 hour) * Applying skills to complete a real-world project * Showcasing work in a professional portfolio Optional: Installing Stable Diffusion and Python (Additional 10 hours) Module 1: Introduction to Stable Diffusion and Python * Overview of Stable Diffusion and Python's significance Module 2: System Requirements * Hardware and software prerequisites for installation Module 3: Installing Python * Step-by-step installation process for different OS Module 4: Configuring Python Environment * Setting up environment variables and package managers Module 5: Installing Stable Diffusion * Downloading and installing the Stable Diffusion package Module 6: Setting Up Development Environment * Configuring IDEs for Python and Stable Diffusion Module 7: Troubleshooting and Common Issues * Identifying and resolving common installation errors Module 8: Best Practices and Recommendations * Managing Python and Stable Diffusion installations Module 9: Practical Examples and Projects * Hands-on exercises demonstrating usage of Stable Diffusion and Python Module 10: Advanced Topics (Optional) * Exploring advanced features and techniques Stable Diffusion UI v2 | A simple 1-click way to install and use https://stable-diffusion-ui.github.io [https://stable-diffusion-ui.github.io] A simple 1-click way to install and use Stable Diffusion on your own computer. ... Get started by downloading the software and running the simple installer. Learning Outcomes: Upon completing the Sketchup and Stable Diffusion Rendering Course, with a focus on AI image rendering, participants will: * Master AI Image Rendering: Gain expertise in using AI-powered rendering techniques to create realistic and high-quality visualizations. * Utilize Sketchup for 3D Modeling: Navigate the software, proficiently use drawing tools, and create detailed 3D models. * Optimize Renderings: Apply AI-based rendering to optimize model visuals, achieving faster rendering times and superior image quality. * Implement AI-driven Lighting and Shadows: Utilize AI algorithms for lighting placement, shadows, and reflections, enhancing realism in renderings. * Create Professional Portfolio: Showcase AI-rendered projects in a professional portfolio, highlighting advanced image rendering skills. Note: The course focuses on AI image rendering using Sketchup and Stable Diffusion techniques, empowering participants with cutting-edge skills for creating exceptional visual representations.

In the past, popular thought treated artificial intelligence (AI) as if it were the domain of science fiction or some far-flung future. In the last few years, however, AI has been given new life. The business world has especially given it renewed interest. However, AI is not just another technology or process for the business to consider - it is a truly disruptive force.

Duration 1 Days 6 CPD hours This course is intended for This course does not have any technical knowledge prerequisites for the learners, besides being proficient in using a computer and the Internet. IT and/or AI knowledge is a benefit but not a hard requirement. Given the rapid development of AI and the broad range of its applications in everyday life, it is crucial for anyone to attend this course to update their digital skills in an ever-changing world. It is expected that all learners have registered for a free account of OpenAI ChatGPT at https://chat.openai.com. Overview Discover how AI relates to other 4th industrial revolution technologies Learn about AI, ML, and associated cognitive services Overview of AI development frameworks, tools and services Evaluate the OpenAI ChatGPT4 / ChatGPT3.5 model features in more detail The core aim of this ?AI for beginners? course is to introduce its audience to Artificial Intelligence (AI) and Machine Learning (ML) technologies and allow them to understand the practical applications of AI in their everyday personal and professional life. Moreover, the course aims to provide a handful of demos and hands-on exercises to allow the learners to familiarize themselves with usage scenarios of OpenAI ChatGPT and other Generative AI (GenAI) models. The content of this course has been created primarily by using the OpenAI ChatGPT model. AI THEORETICAL CONCEPTS. * Introduction to AI, ML, and associated cognitive services (Computer vision, Natural language processing, Speech analysis, Decision making). * How AI relates to other 4th industrial revolution technologies (cloud computing, edge computing, internet of things, blockchain, metaverse, robotics, quantum computing). * AI model classification by utilizing mind maps and the distinctive role of Gen AI models. * Introduction to the OpenAI ChatGPT model and alternative generative AI models. Familiarization with the basics of the ChatGPT interface (https://chat.openai.com). * Talking about Responsible AI: Security, privacy, compliance, copyright, legal challenges, and ethical implications. AI PRACTICAL APPLICATIONS * Overview of AI development frameworks, tools and services. AI aggregators review. * Hand-picked AI tool demos: * a.Workplace productivity and the case of Microsoft 365 Copilot. * b.The content creation industry. Create text, code, images, audio and video with Gen AI. * c.Redefining the education sector with AI-powered learning. * Evaluate the OpenAI ChatGPT4 / ChatGPT3.5 model features in more detail: * a.Prompting and plugin demos. * b.Code interpreter demos. * Closing words. Discussion with an AI model on the future of AI. ADDITIONAL COURSE DETAILS: Nexus Humans AI for beginners 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 AI for beginners 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, along with other AI tools, aims not to replace the human touch in management, but to enhance it. By addressing repetitive, daily tasks, these tools free up managers to concentrate on core responsibilities like strategic decision-making, team development, and innovation. As we move further into the digital age, integrating tools such as ChatGPT isn't a luxury; it's the future of proactive leadership. In this guide, we'll delve into 10 practical ways through which AI can elevate your efficiency and refine the quality of your work. * Gain familiarity with prominent AI tools in the market * Efficiently compose and respond to emails * Generate concise summaries of complex reports and data. * Obtain quick insights, data, and research across varied topics * Streamline the writing of articles, training notes, and posts * Craft interview tests, form relevant questions, and design checklists for the hiring process 1 STREAMLINING EMAILS An inbox can be a goldmine of information but also a significant time drain for managers. Here's how to optimise it: * Drafting responses: Give the AI a brief, and watch it craft a well-structured response. * Sorting and prioritising: By employing user-defined rules and keywords, ChatGPT can flag important emails, ensuring no vital communication slips through the cracks. 2 EFFICIENT REPORT WRITING Reports, especially routine ones, can be time-intensive. Here's a smarter approach: * Automate content: Supply key data points to the AI, and let it weave them into an insightful report. * Proofreading: Lean on ChatGPT for grammar checks and consistency, ensuring each report remains crisp and error-free. 3 RAPID RESEARCH From competitor insights to market trends, research is a pivotal part of management. * Data synthesis: Feed raw data to the AI and receive succinct summaries in return. * Question-answering: Pose specific questions about a dataset to ChatGPT and extract swift insights without diving deep into the entire content. 4 REINVENTING RECRUITMENT Hiring can be a lengthy process. Here's how to make it more efficient: * Resume screening: Equip the AI to spot keywords and qualifications, ensuring that only the most fitting candidates are shortlisted. * Preliminary interviews: Leverage ChatGPT for the initial rounds of interviews by framing critical questions and evaluating the responses. 5 ENHANCING TRAINING Especially for extensive teams, training can be a monumental task. Here's how ChatGPT can assist: * Customised content: Inform the AI of your training goals, and it will draft tailored content suitable for various roles. * PowerPoint design: Create visually appealing slide presentations on any topic in minimal time.

Duration 5 Days 30 CPD hours This course is intended for The skills covered in this course converge on four areas-software development, IT operations, applied math and statistics, and business analysis. Target students for this course should be looking to build upon their knowledge of the data science process so that they can apply AI systems, particularly machine learning models, to business problems. So, the target student is likely a data science practitioner, software developer, or business analyst looking to expand their knowledge of machine learning algorithms and how they can help create intelligent decisionmaking products that bring value to the business. A typical student in this course should have several years of experience with computing technology, including some aptitude in computer programming. This course is also designed to assist students in preparing for the CertNexus Certified Artificial Intelligence (AI) Practitioner (Exam AIP-210) certification Overview In this course, you will develop AI solutions for business problems. You will: Solve a given business problem using AI and ML. Prepare data for use in machine learning. Train, evaluate, and tune a machine learning model. Build linear regression models. Build forecasting models. Build classification models using logistic regression and k -nearest neighbor. Build clustering models. Build classification and regression models using decision trees and random forests. Build classification and regression models using support-vector machines (SVMs). Build artificial neural networks for deep learning. Put machine learning models into operation using automated processes. Maintain machine learning pipelines and models while they are in production Artificial intelligence (AI) and machine learning (ML) have become essential parts of the toolset for many organizations. When used effectively, these tools provide actionable insights that drive critical decisions and enable organizations to create exciting, new, and innovative products and services. This course shows you how to apply various approaches and algorithms to solve business problems through AI and ML, all while following a methodical workflow for developing data-driven solutions. SOLVING BUSINESS PROBLEMS USING AI AND ML * Topic A: Identify AI and ML Solutions for Business Problems * Topic B: Formulate a Machine Learning Problem * Topic C: Select Approaches to Machine Learning PREPARING DATA * Topic A: Collect Data * Topic B: Transform Data * Topic C: Engineer Features * Topic D: Work with Unstructured Data TRAINING, EVALUATING, AND TUNING A MACHINE LEARNING MODEL * Topic A: Train a Machine Learning Model * Topic B: Evaluate and Tune a Machine Learning Model BUILDING LINEAR REGRESSION MODELS * Topic A: Build Regression Models Using Linear Algebra * Topic B: Build Regularized Linear Regression Models * Topic C: Build Iterative Linear Regression Models BUILDING FORECASTING MODELS * Topic A: Build Univariate Time Series Models * Topic B: Build Multivariate Time Series Models BUILDING CLASSIFICATION MODELS USING LOGISTIC REGRESSION AND K-NEAREST NEIGHBOR * Topic A: Train Binary Classification Models Using Logistic Regression * Topic B: Train Binary Classification Models Using k-Nearest Neighbor * Topic C: Train Multi-Class Classification Models * Topic D: Evaluate Classification Models * Topic E: Tune Classification Models BUILDING CLUSTERING MODELS * Topic A: Build k-Means Clustering Models * Topic B: Build Hierarchical Clustering Models BUILDING DECISION TREES AND RANDOM FORESTS * Topic A: Build Decision Tree Models * Topic B: Build Random Forest Models BUILDING SUPPORT-VECTOR MACHINES * Topic A: Build SVM Models for Classification * Topic B: Build SVM Models for Regression BUILDING ARTIFICIAL NEURAL NETWORKS * Topic A: Build Multi-Layer Perceptrons (MLP) * Topic B: Build Convolutional Neural Networks (CNN) * Topic C: Build Recurrent Neural Networks (RNN) OPERATIONALIZING MACHINE LEARNING MODELS * Topic A: Deploy Machine Learning Models * Topic B: Automate the Machine Learning Process with MLOps * Topic C: Integrate Models into Machine Learning Systems MAINTAINING MACHINE LEARNING OPERATIONS * Topic A: Secure Machine Learning Pipelines * Topic B: Maintain Models in Production

Duration 2 Days 12 CPD hours This course is intended for This course is intended for software testers, architects, engineers, or other related roles, who wish to apply AI to software testing practices within their enterprise. While there are no specific pre-requisites for this course, it would be helpful is the attendee has familiarity with basic scripting (Python preferred) and be comfortable with working from the command line (for courses that add the optional hands-on labs). Attendees without basic scripting skills can follow along with the hands-on labs or demos. Overview This course introduces AI and related technologies from a practical applied software testing perspective. Through engaging lecture and demonstrations presented by our expert facilitator, students will explore: Exploring AI Introduction to Machine Learning Introduction to Deep Learning Introduction to Data Science Artificial Intelligence (AI) in Software Testing Implementing AI in Test Automation Innovative AI Test Automation Tools for the Future Implementing AI in Software Testing / AI in Test Automation is an introductory-level course for attendees new to AI, Machine Learning or Deep Learning who wish to automate software testing tasks leveraging AI. The course explores the essentials of AI, ML and DL and how the integrate into IT business operations and initiatives. Then the course moves to specifics about the skills, techniques and tools used to apply AI to common software testing requirements. EXPLORING AI * AI-Initiatives * The Priority: Excellence * AI- Intelligence Types * The Machine Learning Types * The Quality Learning Initiative * The Inception in Academics * AI - Importance & Applications * The Re-visit * Learning Re-visited via AI * Teaching in the world of AI * Exploring AI for Self-Development * AI In Academics Beyond Academics INTRODUCTION TO MACHINE LEARNING * What is Machine Learning? * Why Machine Learning? * Examples - Algorithms behind Machine Learning INTRODUCTION TO DEEP LEARNING * What is Deep Learning? * Why Deep Learning? * Example - Deep Learning Vs Machine Learning INTRODUCTION TO DATA SCIENCE * What is Data Science? * Why Data Science? * Examples - Use Cases of Data Science ARTIFICIAL INTELLIGENCE (AI) IN SOFTWARE TESTING * What is AI in Software Testing? * The Role of AI Testing * Why do we Need AI in Software Testing? * Pros and Cons of AI in Software Testing * Applications of AI in Software Testing * Is it time for Testers or QA Teams to worry about AI? * Automated Testing with Artificial Intelligence IMPLEMENTING AI IN TEST AUTOMATION * Training the AI Bots * Challenges with AI-powered Applications * Examples - Real World use cases using Artificial Intelligence * Demo - Facial Emotion Detection Using Artificial Intelligence * Demo - Text Analysis API Using Artificial Intelligence * Demo - EYE SPY Mobile App Using Artificial Intelligence INNOVATIVE AI TEST AUTOMATION TOOLS FOR THE FUTURE * Tools used for Implementing AI in Automation Testing * What is NEXT? * AI Test Automation Demo using Testim