115 Scientist courses in Porth delivered Live Online

Course Information This highly interactive course will provide guidance on why and how to implement a quality system successfully into the research laboratory. By doing so, you will position your innovation for the success it deserves. But leave things as they are and there is a good chance that your science will not realise its full potential should success, and its consequences, come your way. A quality system in your research laboratory is the most effective and efficient way to: Help scientists work more efficiently Ensure discoveries can be defended Protect the value of intellectual property. This course is particularly aimed at those working in early phase research environments which are not constrained by the regulatory requirements of the Good Practice regulations but are producing intellectual property, testing and/or products for the therapeutic market. For organisational reasons, rather than regulatory ones, this is a place where you need to get it right. The programme is delivered by leaders in the field who, quite simply, ‘have done it’. Whether delegates are at senior management level seeking strategic direction, a laboratory head wishing to deliver science that will stand the test of time or a quality professional thrown in at the deep end, this course will provide key insight and practical guidance to underpin future success. Based on risk based systems, tried and tested over many years in the workplace, the programme will help delegates to define, train, implement and monitor the quality of their research, irrespective of field or discipline. Delegates will learn how to help position their organisation for success. Course content: Delegates will be guided thoughtfully through each key component of the process in a stimulating learning environment. The course probes all avenues of the research quality arena, from an initial understanding of the cultural aspects of the scientific discovery environment, to managing quality in outsourced research programmes. Computer systems and e-data security in the research environment will be discussed and pragmatic solutions described to help manage the ballooning cloud of e-data. In addition, the ever blurring boundary between the regulated and non-regulated research environments will be discussed and delegates given perspective on future developments in the field. With this knowledge, delegates will be able to get it ‘right first time’. Is this course for you? The course is designed for all those involved in the research laboratory quality arena and it has been tailored to meet the needs of scientific management, bench scientists and quality professionals alike. Delegates get immediate access to highly experienced tutors who will share their wisdom and insights in an area where few others have been successful. The course is linked with the RQA guidance which builds on years of experience and forms the foundation of the programme. Tutors Tutors will be comprised of (click the photos for biographies): Louise Handy Director, Handy Consulting Ltd Sandrine Bongiovanni Associate Director in Research and Quality Compliance, Novartis Programme Please note timings may be subject to alteration. Day 1 09:00 Registration 09:10 Welcome and Introductions 09:20 History and Overview of the Field Examples of business and regulatory risks and the consequences of low quality in research. A look at the standards and guidelines that exist. 10:00 The Culture, the Politics and the Scientist's Perspective Understanding research environments, the drivers and the challenges. 10:30 Break 10:45 Workshop - Risk Management Thinking about risk management and prioritisation. Looking at the critical factors for the implementations of a successful quality system. 12:15 Workshop - Feedback 12:45 Lunch 13:45 Personnel, Plans, Procedures, Facilities, Equipment, Materials and Reagents Looking at planning the work, defining procedures in a way which promotes robust science without compromising brilliance and ensuring that all these elements are demonstrably fit for their intended purpose. 14:30 Workshop - Assay Validation How much validation is required at what stage? What do we need to validate an assay? 15:00 Workshop - Feedback 15:15 Research, Work Records, Archives and Research Review Data and records which are accurate, attributable, legally attestable and safe to permit reconstruction experiments and studies. Looking at aspects of the work where there is a chance to review, correct or improve the science, the data and the processes. 16:15 Continual Improvement and Quality Systems Reviewing implementation of a quality system, finding opportunities for improvement, understanding culture change. 16:45 Questions and Answers 17:00 Close of Course Extra Information Course Material This course will be run completely online. You will receive an email with a link to our online system, which will house your licensed course materials and access to the remote event. Please note this course will run in UK timezone. The advantages of this include:   Ability for delegates to keep material on a mobile device Ability to review material at any time pre and post course Environmental benefits – less paper being used per course Access to an online course group to enhance networking. You will need a stable internet connection, a microphone and a webcam. CPD Points 7 Points   Development Level Develop

Duration 1 Days 6 CPD hours This course is intended for The Azure AI Fundamentals course is designed for anyone interested in learning about the types of solution artificial intelligence (AI) makes possible, and the services on Microsoft Azure that you can use to create them. You don?t need to have any experience of using Microsoft Azure before taking this course, but a basic level of familiarity with computer technology and the Internet is assumed. Some of the concepts covered in the course require a basic understanding of mathematics, such as the ability to interpret charts. The course includes hands-on activities that involve working with data and running code, so a knowledge of fundamental programming principles will be helpful. This course introduces fundamentals concepts related to artificial intelligence (AI), and the services in Microsoft Azure that can be used to create AI solutions. The course is not designed to teach students to become professional data scientists or software developers, but rather to build awareness of common AI workloads and the ability to identify Azure services to support them. Prerequisites Prerequisite certification is not required before taking this course. Successful Azure AI Fundamental students start with some basic awareness of computing and internet concepts, and an interest in using Azure AI services. Specifically: Experience using computers and the internet. Interest in use cases for AI applications and machine learning models. A willingness to learn through hands-on exp... 1 - Fundamental AI Concepts Understand machine learning Understand computer vision Understand natural language processing Understand document intelligence and knowledge mining Understand generative AI Challenges and risks with AI Understand Responsible AI 2 - Fundamentals of machine learning What is machine learning? Types of machine learning Regression Binary classification Multiclass classification Clustering Deep learning Azure Machine Learning 3 - Fundamentals of Azure AI services AI services on the Azure platform Create Azure AI service resources Use Azure AI services Understand authentication for Azure AI services 4 - Fundamentals of Computer Vision Images and image processing Machine learning for computer vision Azure AI Vision 5 - Fundamentals of Facial Recognition Understand Face analysis Get started with Face analysis on Azure 6 - Fundamentals of optical character recognition Get started with Vision Studio on Azure 7 - Fundamentals of Text Analysis with the Language Service Understand Text Analytics Get started with text analysis 8 - Fundamentals of question answering with the Language Service Understand question answering Get started with the Language service and Azure Bot Service 9 - Fundamentals of conversational language understanding Describe conversational language understanding Get started with conversational language understanding in Azure 10 - Fundamentals of Azure AI Speech Understand speech recognition and synthesis Get started with speech on Azure 11 - Fundamentals of Azure AI Document Intelligence Explore capabilities of document intelligence Get started with receipt analysis on Azure 12 - Fundamentals of Knowledge Mining with Azure Cognitive Search What is Azure Cognitive Search? Identify elements of a search solution Use a skillset to define an enrichment pipeline Understand indexes Use an indexer to build an index Persist enriched data in a knowledge store Create an index in the Azure portal Query data in an Azure Cognitive Search index 13 - Fundamentals of Generative AI What is generative AI? Large language models What is Azure OpenAI? What are copilots? Improve generative AI responses with prompt engineering 14 - Fundamentals of Azure OpenAI Service What is generative AI Describe Azure OpenAI How to use Azure OpenAI Understand OpenAI's natural language capabilities Understand OpenAI code generation capabilities Understand OpenAI's image generation capabilities Describe Azure OpenAI's access and responsible AI policies 15 - Fundamentals of Responsible Generative AI Plan a responsible generative AI solution Identify potential harms Measure potential harms Mitigate potential harms Operate a responsible generative AI solution Additional course details: Nexus Humans AI-900T00 - Microsoft Azure AI Fundamentals 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-900T00 - Microsoft Azure AI Fundamentals 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.

Duration 1 Days 6 CPD hours This course is intended for The audience for this course includes software developers and data scientists who need to use large language models for generative AI. Some programming experience is recommended, but the course will be valuable to anyone seeking to understand how the Azure OpenAI service can be used to implement generative AI solutions. Note Generative AI is a fast-evolving field of artificial intelligence, and the Azure OpenAI service is subject to frequent changes. The course materials are maintained to reflect the latest version of the service at the time of writing. Azure OpenAI Service provides access to OpenAI's powerful large language models such as GPT; the model behind the popular ChatGPT service. These models enable various natural language processing (NLP) solutions to understand, converse, and generate content. Users can access the service through REST APIs, SDKs, and Azure OpenAI Studio. In this course, you'll learn how to provision Azure OpenAI service, deploy models, and use them in generative AI applications. Prerequisites Familiarity with Azure and the Azure portal. Experience programming with C# or Python. 1 - Get started with Azure OpenAI Service Access Azure OpenAI Service Use Azure OpenAI Studio Explore types of generative AI models Deploy generative AI models Use prompts to get completions from models Test models in Azure OpenAI Studio's playgrounds 2 - Build natural language solutions with Azure OpenAI Service Integrate Azure OpenAI into your app Use Azure OpenAI REST API Use Azure OpenAI SDK 3 - Apply prompt engineering with Azure OpenAI Service Understand prompt engineering Write more effective prompts Provide context to improve accuracy 4 - Generate code with Azure OpenAI Service Construct code from natural language Complete code and assist the development process Fix bugs and improve your code 5 - Generate images with Azure OpenAI Service What is DALL-E? Explore DALL-E in Azure OpenAI Studio Use the Azure OpenAI REST API to consume DALL-E models 6 - Use your own data with Azure OpenAI Service Understand how to use your own data Add your own data source Chat with your model using your own data Additional course details: Nexus Humans AI-050T00: Develop Generative AI Solutions with Azure OpenAI Service 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-050T00: Develop Generative AI Solutions with Azure OpenAI Service 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.

PYTHON BOOTCAMP: This 12-week Python Data Analytics Data Boot Camp is designed to give you a complete skill set required by data analysts . You will be fully fluent and confident as a Python data analyst, with full understanding of Python Programming. From Data, databases, datasets, importing, cleaning, transforming, analysing to visualisation and creating awesome dashboards The course is a practical, instructor-lead program.

Duration 4 Days 24 CPD hours This course is intended for Software engineers concerned with building, managing and deploying AI solutions that leverage Azure AI Services, Azure AI Search, and Azure OpenAI. They are familiar with C# or Python and have knowledge on using REST-based APIs to build computer vision, language analysis, knowledge mining, intelligent search, and generative AI solutions on Azure. AI-102 Designing and Implementing an Azure AI Solution is intended for software developers wanting to build AI infused applications that leverage?Azure AI Services,?Azure AI Search, and?Azure OpenAI. The course will use C# or Python as the programming language. Prerequisites Before attending this course, students must have: Knowledge of Microsoft Azure and ability to navigate the Azure portal Knowledge of either C# or Python Familiarity with JSON and REST programming semantics Recommended course prerequisites AI-900T00: Microsoft Azure AI Fundamentals course 1 - Prepare to develop AI solutions on Azure Define artificial intelligence Understand AI-related terms Understand considerations for AI Engineers Understand considerations for responsible AI Understand capabilities of Azure Machine Learning Understand capabilities of Azure AI Services Understand capabilities of the Azure Bot Service Understand capabilities of Azure Cognitive Search 2 - Create and consume Azure AI services Provision an Azure AI services resource Identify endpoints and keys Use a REST API Use an SDK 3 - Secure Azure AI services Consider authentication Implement network security 4 - Monitor Azure AI services Monitor cost Create alerts View metrics Manage diagnostic logging 5 - Deploy Azure AI services in containers Understand containers Use Azure AI services containers 6 - Analyze images Provision an Azure AI Vision resource Analyze an image Generate a smart-cropped thumbnail 7 - Classify images Provision Azure resources for Azure AI Custom Vision Understand image classification Train an image classifier 8 - Detect, analyze, and recognize faces Identify options for face detection analysis and identification Understand considerations for face analysis Detect faces with the Azure AI Vision service Understand capabilities of the face service Compare and match detected faces Implement facial recognition 9 - Read Text in images and documents with the Azure AI Vision Service Explore Azure AI Vision options for reading text Use the Read API 10 - Analyze video Understand Azure Video Indexer capabilities Extract custom insights Use Video Analyzer widgets and APIs 11 - Analyze text with Azure AI Language Provision an Azure AI Language resource Detect language Extract key phrases Analyze sentiment Extract entities Extract linked entities 12 - Build a question answering solution Understand question answering Compare question answering to Azure AI Language understanding Create a knowledge base Implement multi-turn conversation Test and publish a knowledge base Use a knowledge base Improve question answering performance 13 - Build a conversational language understanding model Understand prebuilt capabilities of the Azure AI Language service Understand resources for building a conversational language understanding model Define intents, utterances, and entities Use patterns to differentiate similar utterances Use pre-built entity components Train, test, publish, and review a conversational language understanding model 14 - Create a custom text classification solution Understand types of classification projects Understand how to build text classification projects 15 - Create a custom named entity extraction solution Understand custom named entity recognition Label your data Train and evaluate your model 16 - Translate text with Azure AI Translator service Provision an Azure AI Translator resource Specify translation options Define custom translations 17 - Create speech-enabled apps with Azure AI services Provision an Azure resource for speech Use the Azure AI Speech to Text API Use the text to speech API Configure audio format and voices Use Speech Synthesis Markup Language 18 - Translate speech with the Azure AI Speech service Provision an Azure resource for speech translation Translate speech to text Synthesize translations 19 - Create an Azure AI Search solution Manage capacity Understand search components Understand the indexing process Search an index Apply filtering and sorting Enhance the index 20 - Create a custom skill for Azure AI Search Create a custom skill Add a custom skill to a skillset 21 - Create a knowledge store with Azure AI Search Define projections Define a knowledge store 22 - Plan an Azure AI Document Intelligence solution Understand AI Document Intelligence Plan Azure AI Document Intelligence resources Choose a model type 23 - Use prebuilt Azure AI Document Intelligence models Understand prebuilt models Use the General Document, Read, and Layout models Use financial, ID, and tax models 24 - Extract data from forms with Azure Document Intelligence What is Azure Document Intelligence? Get started with Azure Document Intelligence Train custom models Use Azure Document Intelligence models Use the Azure Document Intelligence Studio 25 - Get started with Azure OpenAI Service Access Azure OpenAI Service Use Azure OpenAI Studio Explore types of generative AI models Deploy generative AI models Use prompts to get completions from models Test models in Azure OpenAI Studio's playgrounds 26 - Build natural language solutions with Azure OpenAI Service Integrate Azure OpenAI into your app Use Azure OpenAI REST API Use Azure OpenAI SDK 27 - Apply prompt engineering with Azure OpenAI Service Understand prompt engineering Write more effective prompts Provide context to improve accuracy 28 - Generate code with Azure OpenAI Service Construct code from natural language Complete code and assist the development process Fix bugs and improve your code 29 - Generate images with Azure OpenAI Service What is DALL-E? Explore DALL-E in Azure OpenAI Studio Use the Azure OpenAI REST API to consume DALL-E models 30 - Use your own data with Azure OpenAI Service Understand how to use your own data Add your own data source Chat with your model using your own data 31 - Fundamentals of Responsible Generative AI Plan a responsible generative AI solution Identify potential harms Measure potential harms Mitigate potential harms Operate a responsible generative AI solution

Executive AI Coaching: Boost Your Leadership with Generative AI Unlock the power of AI for your business with personalised executive coaching. Paul Addicott-Evans, founder of AECS, offers bespoke 1-on-1 sessions to transform leaders into AI champions. Enhance productivity, drive innovation, and stay ahead in the AI revolution. 20+ years of tech and business expertise. Tailored for C-suite, senior leaders, and entrepreneurs. Elevate your leadership—master generative AI today!

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 Python Machine Learning online instructor led course is an excellent introduction to popular machine learning algorithms. Python Machine Learning 2-day Course Prerequisites: Basic knowledge of Python coding is a pre-requisite. Who Should Attend? This course is an overview of machine learning and machine learning algorithms in Python SciKitLearn. Practical: We cover the below listed algorithms, which is only a small collection of what is available. However, it will give you a good understanding, to plan your Machine Learning project We create, experiment and run machine learning sample code to implement a short selected but representative list of available the algorithms. Course Outline: Supervised Machine Learning: Classification Algorithms: Naive Bayes, Decision Tree, Logistic Regression, K-Nearest Neighbors, Support Vector Machine Regression Algorithms: Linear, Polynomial Unsupervised Machine Learning: Clustering Algorithms: K-means clustering, Hierarchical Clustering Dimension Reduction Algorithms: Principal Component Analysis Latent Dirichlet allocation (LDA) Association Machine Learning Algorithms: Apriori, Euclat Other machine learning Algorithms: Ensemble Methods ( Stacking, bagging, boosting ) Algorithms: Random Forest, Gradient Boosting Reinforcement learning Algorithms: Q-Learning Neural Networks and Deep Leaning Algorithms: Convolutional Network (CNN) Data Exploration and Preprocessing: The first part of a Machine Learning project understands the data and the problem at hand. Data cleaning, data transformation and data pre-processing are covered using Python functions to make data exploration and preprocessing relatively easy. What is included in this Python Machine Learning: Python Machine Learning Certificate on completion Python Machine Learning notes Practical Python Machine Learning exercises and code examples After the course, 1 free, online session for questions or revision Python Machine Learning. Max group size on this Python Machine Learning is 4. Refund Policy No Refunds

Duration 1 Days 6 CPD hours This course is intended for This course is primarily designed for business leaders, consultants, product and project managers, and other decision makers who are interested in unlocking new business opportunities and augmenting existing business processes using generative AI. It's also a great starting point for any business professionals who want to investigate generative AI solutions for their own individual tasks and workflows. This course is also designed to assist students in preparing for the CertNexus GenAIBIZ (Exam GAZ-110) credential. Overview In this course, you will identify ways in which generative AI can bring significant value to the organization. You will: Describe the fundamentals of AI and generative AI. Generate text using AI. Generate code using AI. Generate images and video using AI. Generate audio using AI. Identify the challenges of generative AI. Implement organizational strategies for generative AI. This course is designed to demystify generative AI for business professionals, as well as to trace its power to actionable, real-world business goals. It will give you the essential knowledge of generative AI you'll need to elevate the organization in these exciting times. GenAIBIZÿoffers business professionals with the ability to describe the fundamentals of AI and generative AI; generate text, code, images, video, and audio using generative AI; identify the challenges of generative AI; and implement organizational strategies for generative AI. Exam voucher is included.This course may earn you a Credly badge. Lesson 1: AI Fundamentals Topic A: AI Concepts Topic B: Generative AI Concepts Lesson 2: Generating Text Using AI Topic A: Identify Text Generation Concepts Topic B: Solve Business Problems Using Text Generation Lesson 3: Generating Code Using AI Topic A: Identify Code Generation Concepts Topic B: Solve Business Problems Using Code Generation Lesson 4: Generating Images and Video Using AI Topic A: Identify Image and Video Generation Concepts Topic B: Solve Business Problems Using Image and Video Generation Lesson 5: Generating Audio Using AI Topic A: Identify Audio Generation Concepts Topic B: Solve Business Problems Using Audio Generation Lesson 6: Identifying Challenges of Generative AI Topic A: Identify Shortcomings of Generative AI Topic B: Identify Ethical Risks of Generative AI Topic C: Identify Business Concerns of Generative AI Lesson 7: Implementing Business Strategies for Generative AI Topic A: Apply Best Practices for Generative AI in the Organization Topic B: Evaluate the Results of Generative AI Projects

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