13841 AI courses in London delivered Online

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 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

Aligned with the AIGP certification program, AI Governance Professional Training is for professionals tasked with implementing AI governance and risk management in their organizations. It provides baseline knowledge and strategies for responding to complex risks associated with the evolving AI landscape. This training meets the rapidly growing need for professionals who can develop, integrate and deploy trustworthy AI systems in line with emerging laws and policies. About This Course This training teaches critical artificial intelligence governance concepts that are also integral to the AIGP certification exam. While not purely a 'test prep' course, this training is appropriate for professionals who plan to certify, as well as for those who want to deepen their AI governance knowledge. Both the training and the exam are based on the same body of knowledge.   Module 1: Foundations of artificial intelligence Defines AI and machine learning, presents an overview of the different types of AI systems and their use cases, and positions AI models in the broader socio-cultural context. Module 2: AI impacts on people and responsible AI principles Outlines the core risks and harms posed by AI systems, the characteristics of trustworthy AI systems, and the principles essential to responsible and ethical AI. Module 3: AI development life cycle Describes the AI development life cycle and the broad context in which AI risks are managed. Module 4: Implementing responsible AI governance and risk management Explains how major AI stakeholders collaborate in a layered approach to manage AI risks while acknowledging AI systems' potential societal benefits. Module 5: Implementing AI projects and systems Outlines mapping, planning and scoping AI projects, testing and validating AI systems during development, and managing and monitoring AI systems after deployment. Module 6: Current laws that apply to AI systems Surveys the existing laws that govern the use of AI, outlines key GDPR intersections, and provides awareness of liability reform. Module 7: Existing and emerging AI laws and standards Describes global AI-specific laws and the major frameworks and standards that exemplify how AI systems can be responsibly governed. Module 8: Ongoing AI issues and concerns Presents current discussions and ideas about AI governance, including awareness of legal issues, user concerns, and AI auditing and accountability issues. Accreditation The associated exam is accredited by the IAPP under its ANSI Accreditation Who Should Attend? Any professionals tasked with developing AI governance and risk management in their operations, and anyone pursuing IAPP Artificial Intelligence Governance Professional certification. Prerequisites A general understanding of AI, Corporate Governance, and Business value would be of benefit to participants. Assessment As with all IAPP exams, the AIGP is a 90 question, multiple choice exam to be completed within 150 minutes. Exams are hosted by Pearsonvue and can be taken either remotely, or via any one of hundreds of exam venues globally. A passing score is achieved at 70% Our Guarantee We are an approved IAPP training provider Exam pass guarantee, or retrain until you do, for free What's Included? Participant Guide Study Guide Practice Exam Exam voucher Breakfast, lunch, coffees and snacks (Classroom courses only) Certification Logo

Unlock the potential of AI-driven creative writing with our QuillBot AI Masterclass. Elevate your writing skills and explore advanced features for flawless content creation.

AI in Project Management: The Next Generation of Project Decision Making Project managers need to make critical project decisions on a daily basis. They are confronted with increasing complexities, high ambiguity and the need to process an exponentially growing amount of data and information in order to make informed and good decisions. This leads to an increasing risk of project failure - meanwhile, the project management industry is already challenged with ongoing low project success rates, caused by often massive failures of projects. Project Data Analytics and Artificial Intelligence (AI) are expected to fill the gap by providing analytical and unbiased capabilities that go beyond human possibilities, towards a data-driven and fact-based decision-making approach. While there is little doubt that AI as a trending technology will disrupt the project management practice and augment today's project management capabilities, AI cannot be seen as just another new tool to make project management more effective. Rather, AI will act as a complement to human intelligence, requiring a collaborative approach and, accordingly, a significant change in project culture and peoples' mindset. Today's project decisions are usually driven by human intuition, experience, leadership, and often do not follow any rational logic. Project decision-makers will be required to abandon such an approach and shift to a data-driven, decision-making approach. This session will provide an overview of the expected changes from AI-driven project management, the resulting impact on project decision making and changes in project culture, and what actions can be taken by project professionals to match their beliefs and behaviours with the new project culture. Learning goals: Gain insights into how AI for project management will significantly change decision-making in projects Gain an understanding of how to transition to a new AI-powered project culture

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.

Learn to use cutting-edge language models ChatGPT, Dalle-2, and Midjourney to create high-quality written content and generative art in this course. Discover how to fine-tune these models for specific tasks and explore the ethical implications and future-proofing strategies for using AI in your work.

This course will show delegates how to appraise projects in Excel, incorporate and communicate updates as they happen and ultimately understand how to convert an opportunistic property investment into a core asset that can be sold on.

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.

Course Overview: Dive into the transformative world of Artificial Intelligence (AI) with "ChatGPT for Marketing and Productivity with AI Tools. This course is tailored to unlock the secrets of AI-powered tools in marketing and productivity. According to the McKinsey Global Institute, Artificial Intelligence is an area of study predicted to have an economic impact between $1.49 trillion to $2.95 trillion a year by 2025. It's time to leverage this transformative technology with OpenAI's ChatGPT. In this course, we'll start from the basics, introducing you to OpenAI's ChatGPT, its features, limitations, and how to create an account. You will learn how ChatGPT can generate ideas, qualify and verify information, and produce content in different contexts. In addition, you'll explore a myriad of autonomous AI agents and learn to develop robust methodologies with expert advice. The last part of the course delves into tools and applications like Bing Search, Google Bard, and Speechify that you can use in tandem with ChatGPT. By the end of this course, you'll be well-versed in harnessing the power of AI to enhance marketing strategies and improve productivity. Enrol now and stay ahead of the competition! Key Features of the Course: CPD-certified course. 24/7 learning assistance. Engaging learning materials to enhance your knowledge. Updated and trending content. Who is This Course For? This ChatGPT for Marketing and Productivity with AI Tools course is ideal for marketing professionals, content creators, product managers, or anyone interested in leveraging AI to improve productivity and marketing strategies. What You Will Learn: Our comprehensive ChatGPT for Marketing and Productivity with AI Tools course will help you to: Understanding and setting up an account with ChatGPT. Exploring the limitations and potentials of ChatGPT. The use of ChatGPT in idea generation, content creation, and problem-solving. Interfacing with autonomous AI agents. Use of AI tools for research, summarisation, and voice cloning. Manipulating Microsoft Bing Search, Google Bard, and other applications with ChatGPT. Insight into the future of Generative AI. How to use ChatGPT to conduct research. Why Enrol in This Course: This top-reviewed and recently updated course allows learners to stay at the forefront of the AI revolution. You will gain a competitive edge by developing skills in AI applications for marketing and productivity. Requirements: Participants are expected to have a basic understanding of marketing and productivity processes. Prior experience with AI is not necessary. Career Path: AI Product Manager - £75,000. Content Strategist - £42,000. Marketing Technology Consultant - £60,000. Digital Marketer - £32,000. SEO Specialist - £35,000. Social Media Manager - £45,000. Data Analyst - £40,000. Certification: Upon completing the ChatGPT for Marketing and Productivity with AI Tools course, you will receive a CPD certificate, validating your newly acquired skills and knowledge. Enrol in this course today and enhance your Marketing and Productivity with AI Tools! Course Curriculum 3 sections • 60 lectures • 01:24:00 total length •Unit 01: Start an Account with ChatGPT: 00:02:00 •Unit 02: What the Company OpenAI Say About Itself: 00:02:00 •Unit 03: What OpenAI Say About The Limitations of the Chatbot: 00:02:00 •Unit 04: Chatbot Prompt Examples Given By Open AI: 00:02:00 •Unit 05: Will Chat GPT Be a Paid Application: 00:01:00 •Unit 06: Chat GPT Idea Generation: 00:02:00 •Unit 07: Chat GPT - Idea Qualification and Accuracy: 00:03:00 •Unit 08: ChatGPT - Accuracy and Citations: 00:02:00 •Unit 09: Chat GPT - Creating HTML Instances: 00:01:00 •Unit 10: Chat GPT - How to Solve Specific Business Problems: 00:02:00 •Unit 11: Chat GPT - Statistical Verification of Information: 00:01:00 •Unit 12: Chat GPT - Rewrite Content for Different Contexts: 00:02:00 •Unit 13: ChatGPT - Content Checked With AI: 00:02:00 •Unit 14: ChatGPT - Simplifying Information: 00:01:00 •Unit 15: ChatGPT - How to Ask the Chatbot about Context: 00:01:00 •Unit 16: ChatGPT - How to Cross-Post Queries: 00:01:00 •Unit 17: ChatGPT - How to Narrow Down the Context of Your Query: 00:02:00 •Unit 18: ChatGPT - How to Solve a Business Process: 00:02:00 •Unit 19: ChatGPT - Developing a Methodology From Experts: 00:01:00 •Unit 20: The Future of ChatGPT: 00:01:00 •Unit 01: Autonous AI Agents: 00:01:00 •Unit 02: Connecting to Open AI: 00:01:00 •Unit 03: Getting an OpenAI Key: 00:01:00 •Unit 04: Agent GPT - Autonomous AI: 00:02:00 •Unit 05: GoalGPT - Autonomous Agents: 00:01:00 •Unit 06: Cognosis - Autonomous AI: 00:02:00 •Unit 07: Aomni - Autonomous Agent: 00:01:00 •Unit 08: Durable - Build a Website with AI: 00:01:00 •Unit 09: Eightify Summaries: 00:02:00 •Unit 10: Genei - Do Higher Quality Research with AI: 00:01:00 •Unit 11: Ellicit - Do Higher Quality Research with AI: 00:01:00 •Unit 12: Inciteful - Do Higher Quality Research with AI: 00:02:00 •Unit 13: SciteAI Determine the Credibility of Your Research: 00:01:00 •Unit 14: Eleven Labs - Voice Cloning: 00:02:00 •Unit 15: AgentGPT - Wrap Up and Return: 00:01:00 •Unit 16: Cognosys - Wrap Up and Return: 00:01:00 •Unit 17: Aomni - Wrap Up and Return: 00:01:00 •Unit 18: Goal GPT - Wrap Up and Return: 00:01:00 •Unit 19: Uploading Research Reports to Summarization Applications: 00:01:00 •Unit 20: Perspective on The Future of AI: 00:01:00 •Unit 01: Meta Search Sites: 00:02:00 •Unit 02: SMMRY for Summarzing: 00:01:00 •Unit 03: ChatGPT Plugins Waitlist: 00:01:00 •Unit 04: Using Microsoft Bing Search: 00:02:00 •Unit 05: Using Google Bard: 00:01:00 •Unit 06: Microsoft Word Speech To Text: 00:01:00 •Unit 07: Transcribe Audio in Microsoft Word: 00:02:00 •Unit 08: Speechify: 00:02:00 •Unit 09: Exact Image Creation: 00:01:00 •Unit 10: AI Design Tools: 00:02:00 •Unit 11: Learn How to Prompt: 00:01:00 •Unit 12: Content Improvement: 00:01:00 •Unit 13: Idea Generation: 00:01:00 •Unit 14: Audio Enhancement with Adobe: 00:02:00 •Unit 15: Clean up Audio With Cleaanvoice: 00:01:00 •Unit 16: Notion-AI: 00:01:00 •Unit 17: Pictory: 00:01:00 •Unit 18: Lex: 00:01:00 •Unit 19: ChatPDF: 00:01:00 •Unit 20: Conclusion and the Future of Generatie AI - Searchie: 00:01:00