5219 Model courses

Duration 4 Days 24 CPD hours This course is intended for The audience for this course is data professionals managing data and databases who want to learn about administering the data platform technologies that are available on Microsoft Azure. This course is also valuable for data architects and application developers who need to understand what technologies are available for the data platform with Azure and how to work with those technologies through applications. This course provides students with the knowledge and skills to administer a SQL Server database infrastructure for cloud, on-premises and hybrid relational databases and who work with the Microsoft PaaS relational database offerings. Additionally, it will be of use to individuals who develop applications that deliver content from SQL-based relational databases. Prerequisites In addition to their professional experience, students who take this training should have technical knowledge equivalent to the following courses: AZ-900T00 Microsoft Azure Fundamentals DP-900T00 Microsoft Azure Data Fundamentals 1 - Prepare to maintain SQL databases on Azure Describe Microsoft Intelligent Data Platform roles Understand SQL Server in an Azure virtual machine Design Azure SQL Database for cloud-native applications Explore Azure SQL Database Managed Instance 2 - Deploy IaaS solutions with Azure SQL Explain IaaS options to deploy SQL Server in Azure Understand hybrid scenarios Explore performance and security Explain high availability and disaster recovery options 3 - Deploy PaaS solutions with Azure SQL Explain PaaS options for deploying SQL Server in Azure Explore single SQL database Deploy SQL database elastic pool Understand SQL database hyperscale Examine SQL managed instance Describe SQL Edge 4 - Evaluate strategies for migrating to Azure SQL Understand compatibility level Understand Azure preview features Describe Azure database migration options 5 - Migrate SQL workloads to Azure SQL databases Choose the right SQL Server Instance option in Azure Migrate SQL Server to Azure SQL Database offline Migrate SQL Server to Azure SQL Database online Load and move data to Azure SQL Database 6 - Migrate SQL workloads to Azure Managed Instances Evaluate migration scenarios to SQL Database Managed Instance Migrate to SQL Database Managed Instance Load and Move data to SQL Database Managed Instance 7 - Configure database authentication and authorization Describe Active Directory and Azure Active Directory Describe authentication and identities Describe Security Principals Describe database and object permissions Identify authentication and authorization failures 8 - Protect data in-transit and at rest Explore Transparent Data Encryption Configure server and database firewall rules Explain object encryption and secure enclaves Enable encrypted connections Describe SQL injection Understand Azure Key Vault 9 - Implement compliance controls for sensitive data Explore data classification Explore server and database audit Implement Dynamic Data Masking Implement Row Level security Understand Microsoft Defender for SQL Explore Azure SQL Database Ledger Implement Azure Purview 10 - Describe performance monitoring Describe performance monitoring tools Describe critical performance metrics Establish baseline metrics Explore extended events Describe Azure SQL Insights Explore Query Performance Insight 11 - Configure SQL Server resources for optimal performance Explain how to optimize Azure storage for SQL Server virtual machines Describe virtual machine resizing Optimize database storage Control SQL Server resources 12 - Configure databases for optimal performance Explore database maintenance checks Describe database scoped configuration options Describe automatic tuning Describe intelligent query processing 13 - Explore query performance optimization Understand query plans Explain estimated and actual query plans Describe dynamic management views and functions Explore Query Store Identify problematic query plans Describe blocking and locking 14 - Evaluate performance improvements Describe wait statistics Tune and maintain indexes Understand query hints 15 - Explore performance-based design Describe normalization Choose appropriate data types Design indexes 16 - Automate deployment of database resources Describe deployment models in Azure Automate deployment by using Azure Resource Manager templates and Bicep Automate deployment by using PowerShell Automate deployment by using Azure CLI 17 - Create and manage SQL Agent jobs Create a SQL Server maintenance plan Describe task status notifications 18 - Manage Azure PaaS tasks using automation Explore Elastic jobs Understand Azure Automation Build an automation runbook Automate database workflows by using Logic Apps Monitor automated tasks 19 - Describe high availability and disaster recovery strategies Describe recovery time objective and recovery point objective Explore high availability and disaster recovery options Describe Azure high availability and disaster recovery features for Azure Virtual Machines Describe high availability and disaster recovery options for PaaS deployments Explore an IaaS high availability and disaster recovery solution Describe hybrid solutions 20 - Explore IaaS and PaaS solutions for high availability and disaster recovery Describe failover clusters in Windows Server Configure Always-on availability groups Describe temporal tables in Azure SQL Database Describe active geo-replication for Azure SQL Database Explore auto-failover groups for Azure SQL Database and Azure SQL Managed Instance 21 - Back up and restore databases Back up and restore SQL Server running on Azure virtual machines Back up a SQL Server virtual machine Back up and restore a database using Azure SQL Database Additional course details: Nexus Humans DP-300T00: Administering Microsoft Azure SQL Solutions 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 DP-300T00: Administering Microsoft Azure SQL Solutions 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 Successful students have experience and knowledge in IT operations, including networking, virtualization, identity, security, business continuity, disaster recovery, data platforms, and governance. Students also have experience designing and architecting solutions. Before attending this course, students must have previous experience deploying or administering Azure resources and strong conceptual knowledge of: Azure compute technologies such as VMs, containers and serverless solutions Azure virtual networking to include load balancers Azure Storage technologies (unstructured and databases) General application design concepts such as messaging and high availability This course teaches Azure Solution Architects how to design infrastructure solutions. Course topics cover governance, compute, application architecture, storage, data integration, authentication, networks, business continuity, and migrations. The course combines lecture with case studies to demonstrate basic architect design principles. Prerequisites Before attending this course, students must have previous experience deploying or administering Azure resources and conceptual knowledge of: Azure Active Directory Azure compute technologies such as VMs, containers and serverless solutions Azure virtual networking to include load balancers Azure Storage technologies (unstructured and databases) General application design concepts such as messaging and high availability AZ-104T00 - Microsoft Azure Administrator 1 - Design governance Design for governance Design for management groups Design for subscriptions Design for resource groups Design for resource tags Design for Azure Policy Design for role-based access control (RBAC) Design for Azure landing zones 2 - Design an Azure compute solution Choose an Azure compute service Design for Azure Virtual Machines solutions Design for Azure Batch solutions Design for Azure App Service solutions Design for Azure Container Instances solutions Design for Azure Kubernetes Service solutions Design for Azure Functions solutions Design for Azure Logic Apps solutions 3 - Design a data storage solution for non-relational data Design for data storage Design for Azure storage accounts Design for data redundancy Design for Azure Blob Storage Design for Azure Files Design for Azure managed disks Design for storage security 4 - Design a data storage solution for relational data Design for Azure SQL Database Design for Azure SQL Managed Instance Design for SQL Server on Azure Virtual Machines Recommend a solution for database scalability Recommend a solution for database availability Design security for data at rest, data in motion, and data in use Design for Azure SQL Edge Design for Azure Cosmos DB and Table Storage 5 - Design data integration Design a data integration solution with Azure Data Factory Design a data integration solution with Azure Data Lake Design a data integration and analytic solution with Azure Databricks Design a data integration and analytic solution with Azure Synapse Analytics Design strategies for hot, warm, and cold data paths Design an Azure Stream Analytics solution for data analysis 6 - Design an application architecture Describe message and event scenarios Design a messaging solution Design an Azure Event Hubs messaging solution Design an event-driven solution Design a caching solution Design API integration Design an automated app deployment solution Design an app configuration management solution 7 - Design authentication and authorization solutions Design for identity and access management (IAM) Design for Microsoft Entra ID Design for Microsoft Entra business-to-business (B2B) Design for Azure Active Directory B2C (business-to-customer) Design for conditional access Design for identity protection Design for access reviews Design service principals for applications Design managed identities Design for Azure Key Vault 8 - Design a solution to log and monitor Azure resources Design for Azure Monitor data sources Design for Azure Monitor Logs (Log Analytics) workspaces Design for Azure Workbooks and Azure insights Design for Azure Data Explorer 9 - Design network solutions Recommend a network architecture solution based on workload requirements Design patterns for Azure network connectivity services Design outbound connectivity and routing Design for on-premises connectivity to Azure Virtual Network Choose an application delivery service Design for application delivery services Design for application protection services 10 - Design a solution for backup and disaster recovery Design for backup and recovery Design for Azure Backup Design for Azure blob backup and recovery Design for Azure files backup and recovery Design for Azure virtual machine backup and recovery Design for Azure SQL backup and recovery Design for Azure Site Recovery 11 - Design migrations Evaluate migration with the Cloud Adoption Framework Describe the Azure migration framework Assess your on-premises workloads Select a migration tool Migrate your structured data in databases Select an online storage migration tool for unstructured data Migrate offline data 12 - Introduction to the Microsoft Azure Well-Architected Framework Azure Well-Architected Framework pillars Cost optimization Operational excellence Performance efficiency Reliability Security 13 - Microsoft Azure Well-Architected Framework - Cost Optimization Develop cost-management discipline Design with a cost-efficiency mindset Design for usage optimization Design for rate optimization Monitor and optimize over time 14 - Microsoft Azure Well-Architected Framework - Operational excellence Embrace DevOps culture Establish development standards Evolve operations with observability Deploy with confidence Automate for efficiency Adopt safe deployment practices 15 - Microsoft Azure Well-Architected Framework - Performance efficiency Negotiate realistic performance targets Design to meet capacity requirements Achieve and sustain performance Improve efficiency through optimization 16 - Microsoft Azure Well-Architected Framework - Reliability Design for business requirements Design for resilience Design for recovery Design for operations Keep it simple 17 - Microsoft Azure Well-Architected Framework - Security Plan your security readiness Design to protect confidentiality Design to protect integrity Design to protect availability Sustain and evolve your security posture 18 - Getting started with the Microsoft Cloud Adoption Framework for Azure Customer narrative Common blockers 19 - Prepare for successful cloud adoption with a well-defined strategy Customer narrative Capture strategic motivation Define objectives and key results Evaluate financial considerations Understand technical considerations Create a business case 20 - Prepare for cloud adoption with a data-driven plan Customer narrative 21 - Choose the best Azure landing zone to support your requirements for cloud operations Customer narrative Common operating models Design areas for Azure landing zones Design principles for Azure landing zones Journey to the target architecture Choose an Azure landing zone option Deploy the Azure landing zone accelerator Enhance your landing zone 22 - Migrate to Azure through repeatable processes and common tools Customer narrative Migration process Migration tools Common tech platforms 23 - Address tangible risks with the Govern methodology of the Cloud Adoption Framework for Azure Customer narrative Govern methodology Corporate policies Governance disciplines Deploy a cloud governance foundation The Cost Management discipline 24 - Ensure stable operations and optimization across all supported workloads deployed to the cloud Establish business commitments Deploy an operations baseline Protect and recover Enhance an operations baseline Manage platform and workload specialization 25 - Innovate applications by using Azure cloud technologies Follow the innovation lifecycle Azure technologies for the build process Infuse your applications with AI Azure technologies for measuring business impact Azure technologies for the learn process 26 - Prepare for cloud security by using the Microsoft Cloud Adoption Framework for Azure Customer narrative Methodology Security roles and responsibilities Simplify compliance and security Simplify security implementation Security tools and policies Additional course details: Nexus Humans AZ-305T00: Designing Microsoft Azure Infrastructure Solutions 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 AZ-305T00: Designing Microsoft Azure Infrastructure Solutions 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 3 Days 18 CPD hours This course is intended for CxO?s IT Managers/ Directors Senior Project Officers Project & Program Coordinator/Managers Operations Managers Quality Managers Business Analysts Engineering Managers IT Infrastructure Managers Internal Consultants Professional Consultants Overview Change and the individual Change and the organization Communication and stakeholder engagement Change practice Dealing with change and more importantly, the impact of change is a high priority for all organisations. The Change Management Certification has been developed by APMG in partnership with the Change Management Institute (CMI), an independent, global professional association of change managers. Together they have developed a professional ?body of knowledge? for the discipline of change management. This body of knowledge now provides an independent benchmark for the professional knowledge expected of an effective change manager. APMG?s refreshed Change Management certification is fully aligned with the change management body of knowledge. Prerequisites There is no prerequisite to attending this foundation course, although it is recommended that candidates should have a good understanding of business practices. 1 - Change and the Organization Drivers for change Developing a vision Culture and climate Emergent change and lifecycle Organizational metaphors Models of change Roles required for change 2 - Stakeholders Principles Identification Analysis Influencing and listening Emotion and demonstration Communications Cognitive biases Remaining people focused Improving Communications Communications channels Collaboration Communications Planning Larger workshops 2 - Change Impact Assessing impact McKinsey 7 S Stakeholder impact assessment Assessing change readiness Large change ? how to staff Building a change team Preparing for resistance Building team effectiveness 4 - Individual Change Learning theory Motivation Change Curve Personality differences

This programme has been specifically designed to help experienced trainers, facilitators and coaches use Everything DiSC and the Five Behaviours assessments, and deliver workshops, with their own clients and in-house teams.

Duration 5 Days 30 CPD hours This course is intended for This course is intended for existing IT professionals who have some networking knowledge and experience and are looking for a single course that provides insight into core and advanced networking technologies in Windows Server. This audience would typically include: Network administrators who are looking to reinforce existing skills and learn about new networking technology changes and functionality in Windows Server. System or Infrastructure Administrators with general networking knowledge who are looking to gain core and advanced networking knowledge and skills on Windows Server. Overview Plan and implement an IPv4 network. Implement Dynamic Host Configuration Protocol (DHCP). Implement IPv6. Implement Domain Name System (DNS). Implement and manage IP address management (IPAM). Plan for remote access. Implement DirectAccess. Implement virtual private networks (VPNs). Implement networking for branch offices. Configure advanced networking features. Implement Software Defined Networking. 55343A is the Community Courseware equivalent of retired Legacy Course 20741BC - Networking with Windows Server 2016. This 5-day classroom-based course provides the fundamental networking skills required to deploy and support Windows Server in most organizations. It covers IP fundamentals, remote access technologies, and more advanced content including Software Defined Networking. Although this course and the associated labs are written for Windows Server 2022, the skills taught will also be backwards compatible for Server 2016 and Server 2019. Prerequisites In addition to professional experience, students who attend this training should already have the following technical knowledge: Experience working with Windows Server Knowledge of the Open Systems Interconnection (OSI) model Understanding of core networking infrastructure components and technologies such as cabling, routers and switches Familiarity with networking topologies and architectures such as local area networks (LANs), wide area networks (WANs) and wireless networking Some basic knowledge of the TCP/IP protocol stack, addressing and name resolution Experience with and knowledge of virtualization Hands-on experience working with the Windows client operating systems such as Windows 10 or Windows 11 1 - Planning and implementing an IPv4 network Planning IPv4 addressing Configuring an IPv4 host Managing and troubleshooting IPv4 network connectivity 2 - Implementing DHCP Overview of the DHCP server role Deploying DHCP Managing and troubleshooting DHCP 3 - Implementing IPv6 Overview of IPv6 addressing Configuring an IPv6 host Implementing IPv6 and IPv4 coexistence Transitioning from IPv4 to IPv6 4 - Implementing DNS Implementing DNS servers Configuring zones in DNS Configuring name resolution between DNS zones Configuring DNS integration with Active Directory Domain Services (AD DS) Configuring advanced DNS settings 5 - Implementing and managing IPAM Overview of IPAM Deploying IPAM Managing IP address spaces by using IPAM 6 - Remote access in Windows Server Overview of remote access Implementing the Web Application Proxy 7 - Implementing DirectAccess Overview of DirectAccess Implementing DirectAccess by using the Getting Started Wizard Implementing and managing an advanced DirectAccess infrastructure 8 - Implementing VPNs Planning VPNs Implementing VPNs 9 - Implementing networking for branch offices Networking features and considerations for branch offices Implementing Distributed File System (DFS) for branch offices Implementing BranchCache for branch offices 10 - Configuring advanced networking features Overview of high performance networking features Configuring advanced Microsoft Hyper-V networking features 11 - Implementing Software Defined Networking Overview of SDN. Implementing network virtualization Implementing Network Controller

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

Portrait drawing for beginners and the more experienced from a model.

Duration 1 Days 6 CPD hours This course is intended for The primary audience for this course is data professionals who are familiar with data modeling, extraction, and analytics. It is designed for professionals who are interested in gaining knowledge about Lakehouse architecture, the Microsoft Fabric platform, and how to enable end-to-end analytics using these technologies. Job role: Data Analyst, Data Engineer, Data Scientist Overview Describe end-to-end analytics in Microsoft Fabric Describe core features and capabilities of lakehouses in Microsoft Fabric Create a lakehouse Ingest data into files and tables in a lakehouse Query lakehouse tables with SQL Configure Spark in a Microsoft Fabric workspace Identify suitable scenarios for Spark notebooks and Spark jobs Use Spark dataframes to analyze and transform data Use Spark SQL to query data in tables and views Visualize data in a Spark notebook Understand Delta Lake and delta tables in Microsoft Fabric Create and manage delta tables using Spark Use Spark to query and transform data in delta tables Use delta tables with Spark structured streaming Describe Dataflow (Gen2) capabilities in Microsoft Fabric Create Dataflow (Gen2) solutions to ingest and transform data Include a Dataflow (Gen2) in a pipeline This course is designed to build your foundational skills in data engineering on Microsoft Fabric, focusing on the Lakehouse concept. This course will explore the powerful capabilities of Apache Spark for distributed data processing and the essential techniques for efficient data management, versioning, and reliability by working with Delta Lake tables. This course will also explore data ingestion and orchestration using Dataflows Gen2 and Data Factory pipelines. This course includes a combination of lectures and hands-on exercises that will prepare you to work with lakehouses in Microsoft Fabric. Introduction to end-to-end analytics using Microsoft Fabric Explore end-to-end analytics with Microsoft Fabric Data teams and Microsoft Fabric Enable and use Microsoft Fabric Knowledge Check Get started with lakehouses in Microsoft Fabric Explore the Microsoft Fabric Lakehouse Work with Microsoft Fabric Lakehouses Exercise - Create and ingest data with a Microsoft Fabric Lakehouse Use Apache Spark in Microsoft Fabric Prepare to use Apache Spark Run Spark code Work with data in a Spark dataframe Work with data using Spark SQL Visualize data in a Spark notebook Exercise - Analyze data with Apache Spark Work with Delta Lake Tables in Microsoft Fabric Understand Delta Lake Create delta tables Work with delta tables in Spark Use delta tables with streaming data Exercise - Use delta tables in Apache Spark Ingest Data with DataFlows Gen2 in Microsoft Fabric Understand Dataflows (Gen2) in Microsoft Fabric Explore Dataflows (Gen2) in Microsoft Fabric Integrate Dataflows (Gen2) and Pipelines in Microsoft Fabric Exercise - Create and use a Dataflow (Gen2) in Microsoft Fabric

Duration 3 Days 18 CPD hours This course is intended for This course is aimed at people in senior roles including CIOs, chief digital officers and other aspiring CxOs, as well as consultants and others involved in digital transformations, service delivery and strategic delivery. Overview By the end of this course, you will understand: The internal and external factors to consider while crafting digital strategy How IT strategy differs from digital strategy and how they can be integrated Creating a digital strategy that achieves the most value from digital Implementing and sustaining digital strategy Developing and nurturing digital capabilities for continual business innovation and value co-creation This course takes you on a digital strategy journey. Its iterative, eight-step model moves from ?vision? through to ?actions? and is about creating sustainable, digital momentum. You experience the four key capabilities to develop a holistic, digital capability framework: digital leadership, managing innovation and emerging technologies, risk management and structuring a digital enterprise. This class includes an exam voucher. Prerequisites Delegates attending this course must have successfully achieved the ITIL 4 Foundation Qualification; your certificate must be presented as documentary evidence to gain admission to this course. Although there is no mandatory requirement, ideally candidates should have at least two years professional experience working in IT Service Management. 1 - ITIL GUIDING PRINCIPLES TO ALL ASPECTS OF DIGITAL AND IT STRATEGY Focus on Value Start Where You Are Progress Iteratively with Feedback Collaborate and Promote Visibility Think and Work Holistically Keep It Simple and Practical Optimise and Automate 2 - LEVERAGE DIGITAL STRATEGY TO REACT TO DIGITAL DISRUPTION Digital Technology Digital Business Digital Organisation Digitisation Digital Transformation Business Strategy and Business Models Digital and IT Strategy Products Services Relationship Between Digital, IT Strategy and Components of ITIL SVS. 3 - RELATIONSHIP BETWEEN CONCEPTS OF DIGITAL AND IT STRATEGY, SERVICE VALUE SYSTEM AND SERVICE VALUE CHAIN Environmental Analysis External Analysis: PESTLE Internal Analysis: Four Dimensions of Service Management 4 - HOW AN ORGANISATION USES DIGITAL AND IT STRATEGY TO REMAIN VIABLE IN ENVIRONMENTS How an Organisation?s Viability is Related to Agile, Resilient, Lean, Continuous and Co-Creational it is How to Analyse the VUCA Factors and Address them in a Digital and IT Strategy Organisation?s Position in a Particular Market or Industry Digital Positioning Tool to Determine Appropriate Position for a Digital Organization 5 - EXPLAIN AND COMPARE THREE LEVELS OF DIGITAL DISRUPTION Ecosystem Industry/Market Organisational Influenced factors Achieving Customer/Market Relevance Achieving Operational Excellence Internal and External Focus Balanced Approach 6 - STRATEGIC APPROACHES BY DIGITAL AND IT TO ACHIEVE CUSTOMER/MARKET RELEVANCE AND OPERATIONAL EXCELLENCE How to Apply Approaches to Achieve Customer/Market Relevance Customer Journeys Omnichannel Delivery and Support Context-Sensitive Delivery and Support Customer Analytics Customer Feedback and 360ø Approaches How to Achieve Operational Excellence in the Four Dimensions of Service Management Understand the Financial Aspects of Digital and IT Strategy in Terms of the Following Financial Policies Portfolio Optimization Funding Projects, Products and Services Balancing Cost of Innovation and Operation Charging Models Assess Strategic Approaches for Digital Organizations 7 - RISKS AND OPPORTUNITIES OF DIGITAL AND IT STRATEGY Concept of Risk Management in the Context of a Digital Organisation Context of Digital and IT Strategy Identify Risk Assess Risk Concept of Risk Posture and Show How to Determine an Acceptable Balance Between Opportunity and Risk Explain the Concept of Innovation, Including its Key Elements and Techniques Apply Techniques to Develop and Maintain a Culture of Innovation 8 - STEPS AND TECHNIQUES INVOLVED IN DEFINING AND ADVOCATING FOR DIGITAL AND IT STRATEGY How to Use Digital Readiness Assessment to Perform Gap Analysis Between an Organisation?s Current and Desired Positions Approaches for Scraping Data from Dynamic Websites How to Define and Communicate a Vision and a Strategy How to Use Business Cases to Advocate for a Digital and IT Strategy 9 - IMPLEMENTATION OF A DIGITAL AND IT STRATEGY How to Define Operating Models for Digital Organisations Major Skills Required of Leaders in Digital Organisation Apply Approaches to Strategy Coordination and Implementation: Large-Scale Transformation Incremental Transformation Mergers and Acquisitions Individual Changes Approaches to POMs (Parallel Operating Models) How to Assess Success of a Digital and IT Strategy Typical Activities of a Digital Transformation Programme

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