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Reasons to attendHow to ensure a successful clinical trial within timelines and budget? This Clinical Project Management training is a blended course (eLearning + Classroom or Webinars) designed to introduce the ins and outs of managing clinical research projects. The clinical study setting allows you to implement this knowledge immediately within your research projects.What's included? Documents and materials related to this course are included Globally recognised certificates awarded after test completion This course has been granted PharmaTrain Recognition

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 4 Days 24 CPD hours This course is intended for This course is designed for data scientists with existing knowledge of Python and machine learning frameworks like Scikit-Learn, PyTorch, and Tensorflow, who want to build and operate machine learning solutions in the cloud. Overview Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring in Microsoft Azure. Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring with Azure Machine Learning and MLflow. Prerequisites Creating cloud resources in Microsoft Azure. Using Python to explore and visualize data. Training and validating machine learning models using common frameworks like Scikit-Learn, PyTorch, and TensorFlow. Working with containers AI-900T00: Microsoft Azure AI Fundamentals is recommended, or the equivalent experience. 1 - Design a data ingestion strategy for machine learning projects Identify your data source and format Choose how to serve data to machine learning workflows Design a data ingestion solution 2 - Design a machine learning model training solution Identify machine learning tasks Choose a service to train a machine learning model Decide between compute options 3 - Design a model deployment solution Understand how model will be consumed Decide on real-time or batch deployment 4 - Design a machine learning operations solution Explore an MLOps architecture Design for monitoring Design for retraining 5 - Explore Azure Machine Learning workspace resources and assets Create an Azure Machine Learning workspace Identify Azure Machine Learning resources Identify Azure Machine Learning assets Train models in the workspace 6 - Explore developer tools for workspace interaction Explore the studio Explore the Python SDK Explore the CLI 7 - Make data available in Azure Machine Learning Understand URIs Create a datastore Create a data asset 8 - Work with compute targets in Azure Machine Learning Choose the appropriate compute target Create and use a compute instance Create and use a compute cluster 9 - Work with environments in Azure Machine Learning Understand environments Explore and use curated environments Create and use custom environments 10 - Find the best classification model with Automated Machine Learning Preprocess data and configure featurization Run an Automated Machine Learning experiment Evaluate and compare models 11 - Track model training in Jupyter notebooks with MLflow Configure MLflow for model tracking in notebooks Train and track models in notebooks 12 - Run a training script as a command job in Azure Machine Learning Convert a notebook to a script Run a script as a command job Use parameters in a command job 13 - Track model training with MLflow in jobs Track metrics with MLflow View metrics and evaluate models 14 - Perform hyperparameter tuning with Azure Machine Learning Define a search space Configure a sampling method Configure early termination Use a sweep job for hyperparameter tuning 15 - Run pipelines in Azure Machine Learning Create components Create a pipeline Run a pipeline job 16 - Register an MLflow model in Azure Machine Learning Log models with MLflow Understand the MLflow model format Register an MLflow model 17 - Create and explore the Responsible AI dashboard for a model in Azure Machine Learning Understand Responsible AI Create the Responsible AI dashboard Evaluate the Responsible AI dashboard 18 - Deploy a model to a managed online endpoint Explore managed online endpoints Deploy your MLflow model to a managed online endpoint Deploy a model to a managed online endpoint Test managed online endpoints 19 - Deploy a model to a batch endpoint Understand and create batch endpoints Deploy your MLflow model to a batch endpoint Deploy a custom model to a batch endpoint Invoke and troubleshoot batch endpoints

Duration 3 Days 18 CPD hours This course is intended for This course is intended for IT professionals who are experienced in general Windows Server and Windows Client administration. Students should have a foundational knowledge of Windows PowerShell, which they can obtain by taking course 10961C: Automating Administration with Windows PowerShell. In addition, this course provides scripting guidance for Microsoft Azure administrators and developers who support development environments and deployment processes. Overview After completing this course, you will be able to: Create advanced functions. Use Microsoft .NET Framework and REST API in Windows PowerShell. Handle script errors. Use XML, JSON, and custom formatted data. Manage Microsoft Azure resources Analyze and debug scripts Understand Windows PowerShell workflow. This course teaches students how to automate administrative tasks using PowerShell. Students will learn crucial scripting skills such as creating advanced functions, writing controller scripts, and handling script errors. Candidates will learn how to use PowerShell when working with Microsoft Azure, SQL Server, Active Directory, IIS, Windows PowerShell Workflow, .NET resources, the REST API and XML, CSV & JSON formatted data files.This course replaces retired Microsoft course 10962. Module 1: Creating advanced functions Lesson 1: Converting a command into an advanced function Lesson 2: Creating a script module Lesson 3: Defining parameter attributes and input validation Lesson 4: Writing functions that accept pipeline input Lesson 5: Producing complex pipeline output Lesson 6: Using comment-based Help Lesson 7: Using Whatif and Confirm parameters Module 2: Using Microsoft .NET Framework and REST API in Windows PowerShell Lesson 1: Using .NET Framework in PowerShell Lesson 2: Using REST API in PowerShell Module 3: Writing controller scripts Lesson 1: Understanding controller scripts Lesson 2: Writing controller scripts with a user interface Lesson 3: Writing controller scripts that create reports Module 4: Handling script errors Lesson 1: Understanding error handling Lesson 2: Handling errors in a script Module 5: Using XML, JSON, and custom-formatted data Lesson 1: Working with XML formatted data Lesson 2: Working with JSON formatted data Lesson 3: Working with custom-formatted data Module 6: Enhancing server management with Desired State Configuration and Just Enough Administration Lesson 1: Implementing Desired State Configuration Lesson 2: Implementing Just Enough Administration Module 7: Analyzing and debugging scripts Lesson 1: Debugging in Windows PowerShell Lesson 2: Analyzing and debugging an existing script Module 8: Understanding Windows PowerShell Workflow Lesson 1: Understanding Windows PowerShell Workflows Lesson 2: Running Windows PowerShell Workflows

Resilience is the ability to take the challenges and changes of life in your stride and say yes to the opportunities that excite you.

Duration 3 Days 18 CPD hours This course is intended for This course is designed for Administrators who need to setup, configure and manage SharePoint Online as part of their Office 365 Administration. Overview After completing this course, students will gain the skills to: - Understand the architecture of SharePoint Online - Have knowledge of all the components in SharePoint Online - Have on hands on experience configuring the components of SharePoint Online - Have hands on experience configuring the options - Work with Site Collections and storage options - Manage user profiles and social profiling - Understand and configure data connectivity in SharePoint Online - Build a taxonomy structure - Understand and configure Search in SharePoint Online - Configure and deploy apps - Understand and define Enterprise content management and data loss prevention. - Configure additional options and features in SharePoint Online such as Information Rights Management This course will introduce the audience to SharePoint Online Administration in Office 365 and explain and demonstrate the configuration options for SharePoint Online. The course is appropriate for existing SharePoint on-premises administrators and new administrators to Office 365 who need to understand how to correctly setup SharePoint Online for their company. The course will also help SharePoint on-premise administrators understand the differences between SharePoint on-premises and SharePoint Online. 1 - INTRODUCTION TO OFFICE 365 AND SHAREPOINT ONLINE Introduction to the Office 365 Administration Center Configure Reporting Accessing SharePoint management tools Accessing security and compliancy Managing Office 365 and SharePoint Online with PowerShell Comparing On Premises SharePoint with SharePoint Online User identity in Office 365 and SharePoint Online Manging user domains Building Hybrid scenarios OneDrive and Sites redirection Yammer redirection Understand hybrid search Hybrid business data connectivity Hybrid taxonomy 2 - WORKING WITH SITE COLLECTIONS Introduction to classic and modern admin centers Creating Site Collections Defining ownership and security for site collections Configuring Storage Configure External Access to site collections Recovering site collections Configure external sharing Managing site collections with PowerShell 3 - MANAGING USER PROFILES Overview of the profile service Defining profile properties Map profile properties to a term store Creating custom profile properties Managing audiences Creating audiences Managing user profile policies Configure trusted my site host locations Configure preferred search center locations Defining read access permission levels Configuring newsfeed options Setup email notifications Configure my site cleanup 4 - WORKING WITH DATA CONNECTIONS Introduction to Data Connections Overview of PowerApps, Flow and PowerBi Overview of the business connectivity service Introduction to BDC definition files Creating BDC definition files Introduction to the secure store service Configuring the secure store service Creating secure store target application settings Configure connections to cloud services Configure connections to on-premises services Tools to build data connections Creating external content types Building external lists using external data 5 - MANAGING THE TERM STORE Overview of the term store Understanding terms and life cycle management Creating term groups Creating the term store Creating Term Sets in the UI Creating Term Sets via importing via a CSV Creating terms in the UI Creating terms via PowerShell and CSOM Manage terms with synonyms and pinning Configure delegated administration 6 - CONFIGURING SEARCH An Introduction to the search service Classic versus Modern search experience Understanding Managed Properties Create Managed Properties Manage Authoritative pages Understand Result sources Create and configure result sources Understand Query rules Promoting results through query rules Remove search results from the index Exporting search configurations Importing search configurations 7 - CONFIGURING APPS An Introduction to Apps Understanding the App Catalog Building the App catalog Adding Apps to the catalog Add Apps to your SharePoint sites Adding Apps via the marketplace store Manage App licensing Configure store access settings Monitoring app usage 8 - ENTERPRISE CONTENT MANAGEMENT IN SHAREPOINT ONLINE An Introduction to ECM in SharePoint Online Components of ECM Office 365 versus classic compliancy Understanding In-Place records management Configure In-Place records management Understanding the records center Build and configure a records center Understanding the compliancy policy center Build a compliancy policy center and configure policies Discover the security and compliancy center Configure an eDiscovery center Build an eDiscovery case Understand data loss prevention Build a data loss prevention policy and query Working with classification and data governance 9 - MANAGE OPTIONS FOR SHAREPOINT ONLINE Configure OneDrive features Configure use of Yammer or Newsfeeds Understand Information Rights Management Configure Information Rights Management Define site classification options Understand early release options for Office 365 Configure Early release options for your Office 365 tenant Manage Access Control Additional course details: Nexus Humans 55238 SharePoint Online for Administrators 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 55238 SharePoint Online for Administrators 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.

ITIL® 4 Strategist: Direct, Plan and Improve: Virtual In-House Training The ITIL® 4 Strategist: Direct, Plan, and Improve course is based on the ITIL® 4 Strategist Direct, Plan, and Improve candidate syllabus from AXELOS. This course is based on the ITIL® 4 Strategist: Direct, Plan and Improve IT exam specifications from AXELOS. With the help of ITIL® 4 concepts and terminology, exercises, and examples included in the course, candidates acquire the relevant knowledge required to pass the certification exam. This course provides the practical skills necessary to create a 'learning and improving' IT organization, with a strong and effective strategic direction. It was designed to provide practitioners with a practical and strategic method for planning and delivering continual improvement with necessary agility. It covers both practical and strategic elements, making it the universal module that is a key component to both ITIL® 4 Managing Professional and ITIL® 4 Strategic Leader streams. What You Will Learn At the end of this course, participants will be able to: Understand the key concepts of direction, planning, improvement Understand the scope of what is to be directed and/or planned and know how to use key principles and methods of direction and planning in that context Understand the role of GRC and know how to integrate the principles and methods into the service value system Understand and know how to use the key principles and methods of continual improvement for all types of improvements Understand and know how to use the key principles and methods of Communication and Organizational Change Management to direction, planning and improvement Understand and know how to use the key principles and methods of measurement and reporting in direction, planning, and improvement Understand and know how to direct, plan, and improve value streams and practices Course Introduction Let's Get to Know Each Other Course Overview ITIL® 4 Certification Scheme Course Learning Objectives Course Components Course Agenda Exercises Case Study: Axle Car Hire Case Study: HandyPerson on Demand Exam Details Core Concepts of DPI Key Terms Covered in the Module Module Learning Objectives Basics of Direction Basics of Planning Basics of Improvement Other Core Elements DPI through Service Value Chain and Guiding Principles Key Terms Covered in the Module Module Learning Objectives DPI of the SVS DPI of Guiding Principles Role of Direction in Strategy Management Key Terms Covered in the Module Introducing Strategy Management Developing Effective Strategies Implementation of Strategies Key Terms Covered in the Module Module Learning Objectives Managing Risks Making Decisions through Portfolio Management Directing via Governance, Risk, and Compliance (GRC) Introduction to Assessment and Planning Key Terms Covered in the Module Module Learning Objectives Core Concepts of Assessment Conducting Effective Assessments Core Concepts of Planning Assessment and Planning through VSM Key Terms Covered in the Module Module Learning Objectives Introducing VSM Developing Value Stream Maps Knowing More About VSM Measurement, Reporting, and Continual Improvement Key Terms Covered in the Module Module Learning Objectives Measurement and Reporting Alignment of Measurements and Metrics Success Factors and Key Performance Indicators Continual Improvement Measurements and Continual Improvement through Dimensions and SVS Key Terms Covered in the Module Module Learning Objectives Measurements for the Four Dimensions Continual Improvement of the Service Value Chain and Practices OCM Principles and Methods Key Terms Covered in the Module Module Learning Objectives Basics of OCM OCM throughout DPI and Service Value Chain Resistance and Reinforcement Communication Principles and Methods Key Terms Covered in the Module Module Learning Objectives Basics of Effective Communication Communication with Stakeholders SVS Development Using Four Dimensions Key Terms Covered in the Module Module Learning Objectives Organizations and People in the SVS Partners and Suppliers in the SVS Value Streams and Processes in the SVS Information and Technology in the SVS

Duration 3 Days 18 CPD hours This course is intended for This course is for Network Engineers looking to specialize in Azure networking solutions. An Azure Network engineer designs and implements core Azure networking infrastructure, hybrid networking connections, load balance traffic, network routing, private access to Azure services, network security and monitoring. The azure network engineer will manage networking solutions for optimal performance, resiliency, scale, and security. This course teaches Network Engineers how to design, implement, and maintain Azure networking solutions. This course covers the process of designing, implementing, and managing core Azure networking infrastructure, Hybrid Networking connections, load balancing traffic, network routing, private access to Azure services, network security and monitoring. Learn how to design and implement a secure, reliable, network infrastructure in Azure and how to establish hybrid connectivity, routing, private access to Azure services, and monitoring in Azure. Prerequisites Prerequisite courses (or equivalent knowledge and hands-on experience): AZ-104T00 - Microsoft Azure Administrator 1 - Introduction to Azure Virtual Networks Explore Azure Virtual Networks Configure public IP services Design name resolution for your virtual network Enable cross-virtual network connectivity with peering Implement virtual network traffic routing Configure internet access with Azure Virtual NAT 2 - Design and implement hybrid networking Design and implement Azure VPN Gateway Connect networks with Site-to-site VPN connections Connect devices to networks with Point-to-site VPN connections Connect remote resources by using Azure Virtual WANs Create a network virtual appliance (NVA) in a virtual hub 3 - Design and implement Azure ExpressRoute Explore Azure ExpressRoute Design an ExpressRoute deployment Configure peering for an ExpressRoute deployment Connect an ExpressRoute circuit to a virtual network Connect geographically dispersed networks with ExpressRoute global reach Improve data path performance between networks with ExpressRoute FastPath Troubleshoot ExpressRoute connection issues 4 - Load balance non-HTTP(S) traffic in Azure Explore load balancing Design and implement Azure load balancer using the Azure portal Explore Azure Traffic Manager 5 - Load balance HTTP(S) traffic in Azure Design Azure Application Gateway Configure Azure Application Gateway Design and configure Azure Front Door 6 - Design and implement network security Get network security recommendations with Microsoft Defender for Cloud Deploy Azure DDoS Protection by using the Azure portal Deploy Network Security Groups by using the Azure portal Design and implement Azure Firewall Secure your networks with Azure Firewall Manager Implement a Web Application Firewall on Azure Front Door 7 - Design and implement private access to Azure Services Explain virtual network service endpoints Define Private Link Service and private endpoint Integrate private endpoint with DNS Integrate your App Service with Azure virtual networks 8 - Design and implement network monitoring Monitor your networks using Azure monitor Monitor your networks using Azure network watcher