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Explore the world of Artificial Intelligence with our comprehensive Foundations Course. From understanding the basics of AI and essential mathematical principles to delving into advanced topics like Deep Learning, Natural Language Processing, and Robotics – this course equips you with the knowledge and skills needed to navigate the dynamic landscape of AI. Whether you're a student, professional, or enthusiast, join us on a journey to build a solid foundation in AI and develop practical applications that shape the future. Enroll now and empower yourself to contribute to the exciting field of Artificial Intelligence.

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The “ISO 42001:2023 Lead Auditor Course” integrates the principles of ISO 42001:2023, the International Standard for Artificial Intelligence Management, with the methodologies outlined in ISO 19011:2018, the Guidelines for Auditing Management Systems. The course equips participants with the skills and knowledge required to lead Artificial Intelligence audits effectively, ensuring compliance with ISO 42001:2023, and applies the principles of ISO 17011:2017 for conformity assessment bodies.

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

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.

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Duration 5 Days 30 CPD hours This course is intended for A Microsoft Power Platform Functional Consultant is responsible for creating and configuring apps, automations, and solutions. They act as the liaison between users and the implementation team. The functional consultant promotes utilization of solutions within an organization. The functional consultant may perform discovery, engage subject matter experts and stakeholders, capture requirements, and map requirements to features. They implement components of a solution including application enhancements, custom user experiences, system integrations, data conversions, custom process automation, and simple visualizations. This course will teach you to use Microsoft Power Platform solutions to simplify, automate, and empower business processes for organizations in the role of a Functional Consultant. A Microsoft Power Platform Functional Consultant is responsible for creating and configuring apps, automations, and solutions. They act as the liaison between users and the implementation team. The functional consultant promotes utilization of solutions within an organization. The functional consultant may perform discovery, engage subject matter experts and stakeholders, capture requirements, and map requirements to features. They implement components of a solution including application enhancements, custom user experiences, system integrations, data conversions, custom process automation, and simple visualizations. This course may contain a 1-day Applied Workshop. This workshop will allow you to practice your Functional Consultant skills by creating an end-to-end solution to solve a problem for a fictitious company. The solution will include a Microsoft Dataverse database, Power Apps canvas app, and Power Automate flows. Prerequisites Experience as an IT professional or student Working knowledge of Microsoft Power Platform and its key components Knowledge of Microsoft Dataverse (or general data modeling) and security concepts 1 - Describe the business value of the Microsoft Power Platform Explore Microsoft Power Platform Describe the business value of the Power Platform Explore connectors and Microsoft Dataverse Describe how Power Platform works with Microsoft 365 apps and services Explore how Power Platform works with Microsoft Teams Describe how Power Platform works with Microsoft Dynamics 365 apps Describe how Power Platform solutions consume Microsoft Azure services Explore how Microsoft Power Platform apps work together Use Artificial Intelligence to increase productivity 2 - Core components of Power Pages Get started with Power Pages Core tools and components of Power Pages Overview of Power Pages security Overview of Power Pages extensibility 3 - Explore Power Pages templates Site design templates Scenario-based templates Dynamics 365 Power Pages site templates 4 - Explore Power Pages design studio Work with pages Page components Site styling and templates 5 - Explore Power Pages design studio data and security features Data workspace in Power Pages design studio Power Pages security features 6 - Introduction to Power Pages administration Power Pages administrative tools Set up workspace in Power Pages design studio 7 - Get started building with Power BI Use Power BI Building blocks of Power BI Tour and use the Power BI service 8 - Get data with Power BI Desktop Overview of Power BI Desktop Explore Power BI Desktop Connect to data sources Get data from Excel Transform data to include in a report Combine data from multiple sources Clean data to include in a report 9 - Model data in Power BI How to manage your data relationships Create calculated columns Optimize data models Create measures Create calculated tables Explore time-based data 10 - Use visuals in Power BI Create and customize simple visualizations Create slicers Map visualizations Matrices and tables Create scatter, waterfall, and funnel charts Modify colors in charts and visuals Page layout and formatting 11 - Explore data in Power BI Quick insights in Power BI Create and configure a dashboard Ask questions of your data with natural language Create custom Q&A suggestions Share dashboards with your organization Display visuals and tiles in full screen Edit tile details and add widgets Get more space on your dashboard 12 - Publish and share in Power BI Publish Power BI Desktop reports Print and export dashboards and reports Introducing Power BI Mobile Create workspaces in Power BI Build apps Use apps Integrate OneDrive for Business with Power BI Publish to web 13 - Create and manage workspaces in Power BI Distribute a report or dashboard Monitor usage and performance Recommend a development life cycle strategy Troubleshoot data by viewing its lineage Configure data protection 14 - Manage semantic models in Power BI Use a Power BI gateway to connect to on-premises data sources Configure a semantic model scheduled refresh Configure incremental refresh settings Manage and promote semantic models Troubleshoot service connectivity Boost performance with query caching (Premium) 15 - Create dashboards in Power BI Configure data alerts Explore data by asking questions Review Quick insights Add a dashboard theme Pin a live report page to a dashboard Configure a real-time dashboard Set mobile view 16 - Implement row-level security Configure row-level security with the static method Configure row-level security with the dynamic method 17 - Create tables in Dataverse Table characteristics Table relationships Dataverse logic and security Dataverse auditing Dual-write vs. virtual tables 18 - Manage tables in Dataverse Identify tables and table types in Dataverse Create a custom table Enable attachments within a table Licensing requirements for each table type 19 - Create and manage columns within a table in Dataverse Define columns in Microsoft Dataverse Column types in Microsoft Dataverse Add a column to a table Create a primary name column Restrictions that apply to columns in a table Create an auto numbering column Create an alternate key 20 - Create a relationship between tables in Dataverse Relate one or more tables - Introduction Relationship types that are available in Microsoft Dataverse Create a one-to-many relationship between tables Create a many-to-many relationship between tables Edit or delete relationships 21 - Working with choices in Dataverse Define choice column Standard choices column 22 - Get started with security roles in Dataverse Understand environment roles Adding or disabling an environment user Understand security concepts in Dataverse Understand user security roles and security role defaults Check the roles that a user belongs to Configure Dataverse teams for security Configure Dataverse group teams for security 23 - Use administration options for Dataverse Use Microsoft Power Platform Admin Center portal Tenant storage capacity Advanced Customization options in Power Apps Portal Enable and disable auditing 24 - Manage Dynamics 365 model-driven app settings and security Configure role-based security Manage teams and business units Explore settings and customizations 25 - Introduction to Microsoft Power Platform security and governance Identify Microsoft Power Platform environments Data Loss Prevention policies Microsoft Power Platform Center of Excellence Starter Kit 26 - Get started with model-driven apps in Power Apps Introducing model-driven apps Components of model-driven apps Design model-driven apps Incorporate business process flows 27 - Configure forms, charts, and dashboards in model-driven apps Forms overview Form elements Configure multiple forms Use specialized form components Configure views overview Configure grids Create and edit views Configure charts overview Dashboards overview Use interactive streams and tiles 28 - Get started with Power Apps canvas apps Power Apps building blocks Ways to build Power Apps Power Apps related technologies Additional Power Apps related technologies Designing a Power Apps app 29 - Connect to other data in a Power Apps canvas app Overview of the different data sources Work with action-based data sources Power Automate is a companion to Power Apps 30 - How to build the UI in a canvas app in Power Apps Use themes to quickly change the appearance of your app Branding a control Icons Images Personalization Using the tablet or phone form factors 31 - Manage apps in Power Apps Power Apps review 32 - Build your first app with Power Apps and Dataverse for Teams Create your first app with the hero template Customize your app with Power Apps Studio Publish your app Install template apps 33 - Access Dataverse in Power Pages websites Use lists to display multiple Dataverse records Use forms to interact with Dataverse data 34 - Authentication and user management in Power Pages Power Pages authentication settings User registration in Power Pages Authentication management for Power Pages users Power Pages authentication providers 35 - Power Pages maintenance and troubleshooting Power Pages website maintenance Power Pages website troubleshooting 36 - Define and create business rules in Dataverse Define business rules - Introduction Define the components of a business rule Create a business rule 37 - Get started with Power Automate Introducing Power Automate Troubleshoot flows 38 - Use the Admin center to manage environments and data policies in Power Automate Administer flows Export and import flows Learn how to distribute button flows 39 - Use Dataverse triggers and actions in Power Automate Dataverse triggers Query data Create, update, delete, and relate actions 40 - Extend Dataverse with Power Automate Set up a flow and configure its trigger Email Dataverse record Add to-do items Test and run your flow 41 - Introduction to expressions in Power Automate Get started with expressions Notes make things easier Types of functions Write complex expressions 42 - Build your first Power Automate for desktop flow Set up the environment Explore Power Automate for desktop Create your first Power Automate for desktop flow Record Power Automate for desktop actions Edit and test recorded actions 43 - Run a Power Automate for desktop flow in unattended mode Set up an unattended desktop flow Create a new cloud flow that calls an existing flow in unattended mode Perform a test run Best practices 44 - Optimize your business process with process advisor Get familiar with process advisor Create your first recording Edit recordings and group actions Analyze recordings and interpret results Automation recommendations 45 - Get started with Microsoft Copilot Studio bots Get started working with environments Create bots and work with the Microsoft Copilot Studio interface Create topics Test bots Publish bots and analyze performance 46 - Enhance Microsoft Copilot Studio bots Use Power Automate to add actions Transfer conversations to agents by using Omnichannel for Customer Service Create topics for existing support content Analyze bot performance 47 - Manage topics in Microsoft Copilot Studio Work with bot topics Branch a topic Create topics for existing support content Work with system fallback topics Manage topics 48 - Manage Power Virtual Agents Environments in Microsoft Copilot Studio Bot topics permissions Bot entities and flow permissions Monitor and diagnose Administer and manage Export and import bots Authentication 49 - Get started building with Power BI Use Power BI Building blocks of Power BI Tour and use the Power BI service 50 - Get data with Power BI Desktop Overview of Power BI Desktop Explore Power BI Desktop Connect to data sources Get data from Excel Transform data to include in a report Combine data from multiple sources Clean data to include in a report 51 - Model data in Power BI How to manage your data relationships Create calculated columns Optimize data models Create measures Create calculated tables Explore time-based data 52 - Use visuals in Power BI Create and customize simple visualizations Create slicers Map visualizations Matrices and tables Create scatter, waterfall, and funnel charts Modify colors in charts and visuals Page layout and formatting 53 - Explore data in Power BI Quick insights in Power BI Create and configure a dashboard Ask questions of your data with natural language Create custom Q&A suggestions Share dashboards with your organization Display visuals and tiles in full screen Edit tile details and add widgets Get more space on your dashboard 54 - Publish and share in Power BI Publish Power BI Desktop reports Print and export dashboards and reports Introducing Power BI Mobile Create workspaces in Power BI Build apps Use apps Integrate OneDrive for Business with Power BI Publish to web 55 - Manage solutions in Power Apps and Power Automate Add and remove apps, flows, and entities in a solution Edit a solution-aware app, flow, and table Build and deploy a complex solution with flows, apps, and entities Automate solution management 56 - Load/export data and create data views in Dataverse View data in a table Create or edit views of data in a table Load data into a table Export data from a table Add, update, or delete data in a table by using Excel Import data using Power Query Generate a new dataflow from an Excel Template Dataflow and Azure integration 57 - Get started with AI Builder Choose an AI capability Create your first model Ways to use your models 58 - Manage models in AI Builder Model lifecycle Manage model versions Share your models 59 - Use AI Builder in Power Automate AI Builder in Power Automate saves time Advanced usage of AI Builder in Power Automate 60 - Functional Consultant skills Create entity relationship diagrams Create and document mock-ups Document functional requirements and artifacts Complete fit-gap analysis Discuss stakeholder management responsibilities Understand industry accelerators Define Application Lifecycle Management Participate in testing Evaluate options Define connectors Understand Power Apps component framework 61 - Solution Architect series: Plan application lifecycle management for Power Platform Key considerations for ALM Solutions Configuration and reference data Release process ALM with Azure DevOps

Duration 3 Days 18 CPD hours This course is intended for Senior Consultants (both functional and technical) that aspire to be Solution Architects, or current Solution Architects that are new to the role. The Solution Architect is responsible for the successful design, implementation, deployment and adoption of an overall solution. The Solution Architect ensures that the solution meets the customer?s needs now and in the future. In this course, students will learn about decisions a Solution Architect makes during an implementation, covering security, integrations, Power Apps architecture, Power Automate architecture, and more. This course is designed to give you an introduction to the Solution Architect role. Becoming a Solution Architect/Getting to know your customer Define a Solution Architect Role of a Solution Architect on projects Project Methodology Getting to know your customer Group exercise - Getting to know your customer Conceptualizing the design from requirements How to lead the requirement collection effort Using fit gap analysis Pillars of good architecture Blueprinting the solution architecture Group exercise - Design from requirements Project governance and working as a team Solution Architect's role in project governance Techniques for keeping a project on track Scenarios that could cause a project to fail Group exercise - Project governance and working as a team Power Platform Architecture Key Power Platform architecture components Understand how platform design and limits influence solution architectures Updates and feature releases Understand how to communicate how the platform meets customer needs Data Modeling Data model influences Data model strategy Data types Data relationships Group exercise - Data modeling Analytics and artificial intelligence Planning and evaluating requirements Operational reporting Power BI Enterprise BI Pre-built insights and custom AI Power Apps Architecture Discuss options for apps and how to choose where to start Discuss app composition options Using components as part of your app architecture Considerations for including Portals as an app in your architecture Group exercise - Power Apps Architecture topics Application Lifecycle Management (ALM) Microsoft vision and Solution Architect's role in ALM Environment strategies Defning a solution structure for your deliverable Power Automate Architecture Discuss options for automation and custom logic Review considerations for using triggers and common actions Explore using Business Process Flows (BPF) to guide users through business processes Group Exercise - Evaluate scenarios for Power Automate usage Security Modeling Solution Architect's role in security modeling Discovery and learning your client's environment Controlling access to environments and resources Controlling access to CDS Data Group Exercise - Security Modeling Integration Solution Architects role in Integrations What is an integration and why do we need it Platform features that enable integration CDS Event Publishing Scenarios for group discussion Dynamics 365 Applications Architecture Solution Architect's role when deploying Dynamics 365 apps Architecture Considerations for primary apps Group Exercise - App specific working groups evaluate requirements Power Virtual Agents architecture Introduction Chatbot options Chatbot concepts Best practices Integrate chatbots Power Virtual Agents in Microsoft Teams Robotic Process Automation Introduction Power Automate Desktop Recording and editing tasks Running desktop flows Process advisor Testing and Go Live Solution Architect's role with testing and go live Planning for testing Planning for go live

The “ISO 42001:2023 Lead Implementer Course” is designed to provide participants with the knowledge and skills necessary to lead the implementation of an Artificial Intelligence Management System based on ISO 42001:2023. This comprehensive course covers the key principles, requirements, and best practices for establishing and maintaining an effective Artificial Intelligence management system. Participants will learn how to develop, implement, and manage processes that comply with the ISO 42001 standard.

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