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ITIL® 4 Specialist: High Velocity IT: Virtual In-House Training The ITIL® 4 Specialist: High-Velocity IT module is part of the Managing Professional stream for ITIL® 4. Candidates need to pass the related certification exam for working towards the Managing Professional (MP) designation. This course is based on the ITIL® 4 Specialist: High-Velocity 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 module addresses the specifics of digital transformation and helps organizations to evolve towards a convergence of business and technology, or to establish a new digital organization. It was designed to enable practitioners to explore the ways in which digital organizations and digital operating models function in high-velocity environments. Working practices such as Agile and Lean, and technical practices and technologies such as Cloud, Automation, and Automatic Testing are included. What You Will Learn At the end of this course, participants will be able to: Understand concepts regarding the high-velocity nature of the digital enterprise, including the demand it places on IT. Understand the digital product lifecycle in terms of the ITIL operating model. Understand the importance of the ITIL guiding principles and other fundamental concepts for delivering high-velocity IT. Know how to contribute to achieving value with digital products. Course Introduction Let's Get to Know Each Other Course Learning Objectives Target Audience Characteristics ITIL® 4 Certification Scheme Course Components Course Agenda Module-End Exercises Exam Details Introduction to High-Velocity IT High-Velocity IT Digital Technology Digital Organizations Digital Transformation High-Velocity IT Approaches Relevance of High-Velocity IT Approaches High-Velocity IT Approaches in Detail High-Velocity IT Operating Models Introduction ITIL® Perspective High-Velocity IT Aspects High-Velocity IT Applications ITIL® Building Blocks for High-Velocity IT Digital Product Lifecycle Service Value Streams Four Dimensions of Service Management ITIL® Management Practices High-Velocity IT Culture Key Behavior Patterns ITIL® Guiding Principles Supporting Models and Concepts for Purpose Ethics Design Thinking Supporting Models and Concepts for People Reconstructing for Service Agility Safety Culture Stress Prevention Supporting Models and Concepts for Progress Working in Complex Environments Lean Culture ITIL® Continual Improvement Model High-Velocity IT Objectives and Techniques High-Velocity IT Objectives High-Velocity IT Techniques Techniques for Valuable Investments Prioritization Techniques Minimum Viable Products and Services Product / Service Ownership A/B Testing Techniques for Fast Developments Basic Concepts Related to Fast Development Infrastructure as Code Reviews Continual Business Analysis Continuous Integration / Continuous Delivery (CI/CD) Continuous Testing Kanban Techniques for Resilient Operations Introduction to Resilient Operations Technical Debt Chaos Engineering Definition of Done Version Control Algorithmic IT Operations ChatOps Site Reliability Engineering (SRE) Techniques for Co-created Value Basic Concepts of Co-created Value Service Experience Techniques for Assured Conformance DevOps Audit Defense Toolkit DevSecOpsPeer Review

About this Virtual Instructor Led Training (VILT) This 5 half-day Virtual Instructor Led Training (VILT) course will assist energy professionals in the planning and operation of a power system from renewable energy sources. The VILT course will discuss key operating requirements for an integrated, reliable and stable power system. The unique characteristics of renewable energy are discussed from a local, consumer centric and system perspective, bringing to life the ever-changing paradigm in delivering energy to customers. The course will explore the technical challenges associated with interconnecting and integrating hundreds of gigawatts of solar power onto the electricity grid in a safe and reliable way. With references to international case studies, the VILT course will also demonstrate the state of the art methodologies used in forecasting solar power. The flexibility of the invertor-based resources will facilitate higher penetrations of photovoltaic, battery electricity storage systems and demand response while co-optimizing customer resources. The contribution of inverter-based generators that provides voltage support, frequency response and regulation (droop response), reactive power and power quality with a high level of accuracy and fast response will be addressed. Furthermore, this VILT course will also describe how microgrids' controllers can allow for a fully automated energy management. Distributed energy resources are analyzed in detail from a technical and financial aspect and will address the best known cost based methodologies such as project financing and cost recovery. Training Objectives Upon completion of this VILT course, participants will be able to: Learn about renewable energy resources, their applications and methods of analysis of renewable energy issues. Review the operational flexibility of renewable energy at grid level, distribution network and grid edge devices. Understand and analyze energy performance from main renewable energy systems. Get equipped on the insights into forecasting models for solar energy. Predict solar generation from weather forecasts using machine learning. Explore operational aspects of a complex power system with variability from both the supply & demand sides. Manage the impact of the design of a Power Purchase Agreement (PPA) on the power system operation. Target Audience Engineers, planners and operations professionals from the following organizations: Energy aggregators who would like to understand the system operations of renewable energy power plants Renewable energy power system operator Energy regulatory agencies who aim to derive strategies and plans based on the feedback obtained from the power system operations Course Level Basic or Foundation Training Methods The VILT course will be delivered online in 5 half-day sessions comprising 4 hours per day, including time for lectures, discussion, quizzes and short classroom exercises. Course Duration: 5 half-day sessions, 4 hours per session (20 hours in total). Trainer Your first expert course leader is a Utility Executive with extensive global experience in power system operation and planning, energy markets, enterprise risk and regulatory oversight. She consults on energy markets integrating renewable resources from planning to operation. She led complex projects in operations and conducted long term planning studies to support planning and operational reliability standards. Specializing in Smart Grids, Operational flexibilities, Renewable generation, Reliability, Financial Engineering, Energy Markets and Power System Integration, she was recently engaged by the Inter-American Development Bank/MHI in Guyana. She was the Operations Expert in the regulatory assessment in Oman. She is a registered member of the Professional Engineers of Ontario, Canada. She is also a contributing member to the IEEE Standards Association, WG Blockchain P2418.5. With over 25 years with Ontario Power Generation (Revenue $1.2 Billion CAD, I/S 16 GW), she served as Canadian representative in CIGRE, committee member in NSERC (Natural Sciences and Engineering Research Council of Canada), and Senior Member IEEE and Elsevier since the 90ties. Our key expert chaired international conferences, lectured on several continents, published a book on Reliability and Security of Nuclear Power Plants, contributed to IEEE and PMAPS and published in the Ontario Journal for Public Policy, Canada. She delivered seminars organized by the Power Engineering Society, IEEE plus seminars to power companies worldwide, including Oman, Thailand, Saudi Arabia, Malaysia, Indonesia, Portugal, South Africa, Japan, Romania, and Guyana. Your second expert course leader is the co-founder and Director of Research at Xesto Inc. Xesto is a spatial computing AI startup based in Toronto, Canada and it has been voted as Toronto's Best Tech Startup 2019 and was named one of the top 10 'Canadian AI Startups to Watch' as well as one of 6th International finalists for the VW Siemens Startup Challenge, resulting in a partnership. His latest app Xesto-Fit demonstrates how advanced AI and machine learning is applied to the e-commerce industry, as a result of which Xesto has been recently featured in TechCrunch. He specializes in both applied and theoretical machine learning and has extensive experience in both industrial and academic research. He is specialized in Artificial Intelligence with multiple industrial applications. At Xesto, he leads projects that focus on applying cutting edge research at the intersection of spatial analysis, differential geometry, optimization of deep neural networks, and statistics to build scalable rigorous and real time performing systems that will change the way humans interact with technology. In addition, he is a Ph.D candidate in the Mathematics department at UofT, focusing on applied mathematics. His academic research interests are in applying advanced mathematical methods to the computational and statistical sciences. He earned a Bachelor's and MSc in Mathematics, both at the University of Toronto. Having presented at research seminars as well as instructing engineers on various levels, he has the ability to distill advanced theoretical concept to diverse audiences on all levels. In addition to research, our key expert is also an avid traveler and plays the violin. POST TRAINING COACHING SUPPORT (OPTIONAL) To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster. Request for further information about post training coaching support and fees applicable for this. Accreditions And Affliations

About this Virtual Instructor Led Training (VILT) This Virtual Instructor Led Training (VILT) course presents advanced methodologies that implement demand response and energy conservation programs in light of the integration of new technologies, regulatory changes and the accelerated penetration of renewable energy resources. This VILT course provides examples and case studies from North American and European jurisdictions covering the operational flexibilities on the demand side including requirements for new building codes to achieve zero net energy. The course describes a public agency's goals and objectives for conserving and otherwise reducing energy consumption and managing its demand for energy. This course presents the demand response implemented for economics and system security such as system balancing and relieving transmission congestion, or for system adequacy. The course also presents the principal attributes of conservation programs and the associated success criteria. In a system with increased penetration of renewable resources, demand response provides flexibility to system operators, helping them to maintain the reliability and the security of supply. Demand response is presented as a competitive alternative to additional power sources, enhancing competition and liquidity in electricity markets. The unique characteristics are discussed from a local, consumer centric and also from a system perspective bringing to life the ever changing paradigm for delivery energy to customers. Interoperability aspects and standards are discussed, as well as the consumer centric paradigm of Transactive Energy with IOT enabled flexibilities at system level, distribution networks and microgrids. The VILT course introduces the blockchain as a new line of defense against cyber threats and its increasing application in P2P transactions and renewable certificates. Our trainer's industry experience spans three decades with one of the largest Canadian utilities where she led or contributed to large operational studies and energy policies and decades of work with IEEE, NSERC and CIGRE. Our key expert also approaches to the cross sectional, interdisciplinary state of the art methodologies brings real life experience of recent industry developments. Training Objectives Innovative Digital Technologies How systems Facilitate Operational Flexibility on the Demand Side The Ecosystem of Demand Side Management Programs Advanced Machine Learning techniques with examples from CAISO Regulatory Policy Context and how to reduce regulatory barriers Industry Examples from NERC and ENTSO Relevant Industry standards: IEEE and IEC Manage Congestion with Distributed Operational Flexibilities: Grid to Distribution Controls; examples from NERC (NA) and ENTSO (Europe) Grid solutions with IEC 61850 communication protocols Decentralized grid controls The New Grid with accelerated V2G and Microgrids How DSM is and will be applied in Your System: Examples and discussions Target Audience Regulators and government agencies advising on public energy conservation programs All professionals interested in expanding their expertise, or advancing their career, or take on management and leadership roles in the rapidly evolving energy sector Energy professionals implementing demand side management, particularly in power systems with increased renewable penetration, to allow the much needed operational flexibility paramount to maintaining the reliability and stability of the power system and in the same time offering all classes of customers flexible and economical choices Any utility professional interested in understanding the new developments in the power industry Course Level Basic or Foundation Training Methods The VILT course will be delivered online in 5 half-day sessions comprising 4 hours per day, with 2 x 10 minutes break per day, including time for lectures, discussion, quizzes and short classroom exercises. Course Duration: 5 half-day sessions, 4 hours per session (20 hours in total). Trainer Your first expert course leader is a Utility Executive with extensive global experience in power system operation and planning, energy markets, enterprise risk and regulatory oversight. She consults on energy markets integrating renewable resources from planning to operation. She led complex projects in operations and conducted long term planning studies to support planning and operational reliability standards. Specializing in Smart Grids, Operational flexibilities, Renewable generation, Reliability, Financial Engineering, Energy Markets and Power System Integration, she was recently engaged by the Inter-American Development Bank/MHI in Guyana. She was the Operations Expert in the regulatory assessment in Oman. She is a registered member of the Professional Engineers of Ontario, Canada. She is also a contributing member to the IEEE Standards Association, WG Blockchain P2418.5. With over 25 years with Ontario Power Generation (Revenue $1.2 Billion CAD, I/S 16 GW), she served as Canadian representative in CIGRE, committee member in NSERC (Natural Sciences and Engineering Research Council of Canada), and Senior Member IEEE and Elsevier since the 90ties. Our key expert chaired international conferences, lectured on several continents, published a book on Reliability and Security of Nuclear Power Plants, contributed to IEEE and PMAPS and published in the Ontario Journal for Public Policy, Canada. She delivered seminars organized by the Power Engineering Society, IEEE plus seminars to power companies worldwide, including Oman, Thailand, Saudi Arabia, Malaysia, Indonesia, Portugal, South Africa, Japan, Romania, and Guyana. Your second expert course leader is the co-founder and Director of Research at Xesto Inc. Xesto is a spatial computing AI startup based in Toronto, Canada and it has been voted as Toronto's Best Tech Startup 2019 and was named one of the top 10 'Canadian AI Startups to Watch' as well as one of 6th International finalists for the VW Siemens Startup Challenge, resulting in a partnership. His latest app Xesto-Fit demonstrates how advanced AI and machine learning is applied to the e-commerce industry, as a result of which Xesto has been recently featured in TechCrunch. He specializes in both applied and theoretical machine learning and has extensive experience in both industrial and academic research. He is specialized in Artificial Intelligence with multiple industrial applications. At Xesto, he leads projects that focus on applying cutting edge research at the intersection of spatial analysis, differential geometry, optimization of deep neural networks, and statistics to build scalable rigorous and real time performing systems that will change the way humans interact with technology. In addition, he is a Ph.D candidate in the Mathematics department at UofT, focusing on applied mathematics. His academic research interests are in applying advanced mathematical methods to the computational and statistical sciences. He earned a Bachelor's and MSc in Mathematics, both at the University of Toronto. Having presented at research seminars as well as instructing engineers on various levels, he has the ability to distill advanced theoretical concept to diverse audiences on all levels. In addition to research, our key expert is also an avid traveler and plays the violin. POST TRAINING COACHING SUPPORT (OPTIONAL) To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster. Request for further information about post training coaching support and fees applicable for this. Accreditions And Affliations

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ITIL® 4 Specialist: Drive Stakeholder Value: Virtual In-House Training The ITIL® 4 Specialist: Drive Stakeholder Value module is part of the Managing Professional stream for ITIL 4. Candidates need to pass the related certification exam for working towards the Managing Professional (MP) designation. This course is based on the ITIL® 4 Specialist: Drive Stakeholder Value 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. What You Will Learn The learning objectives of the course are based on the following learning outcomes of the ITIL® 4 Specialist: Drive Stakeholder Value exam specification: Understand how customer journeys are designed Know how to target markets and stakeholders Know how to foster stakeholder relationships Know how to shape demand and define service offerings Know how to align expectations and agree on details of services Know how to onboard and offboard customers and users Know how to act together to ensure continual value co-creation (service consumption / provisioning) Know how to realize and validate service value Customer Journey Purpose of the Module Purpose of Mastering the Customer Journey Touchpoints and Service Interactions Module Topics Mapping the Customer Journey Designing the Customer Journey Measuring and Improving the Customer Journey Customer Journey Step 1: Explore Purpose of the Module Purpose of the Explore Step Module Topics Understanding Service Consumers Understanding Service Providers Understanding and Targeting Markets Customer Journey Step 2: Engage Purpose of the Module Purpose of the Engage Step Aspects of Service Value Module Topics Service Relationship Types Building Service Relationships Building and Sustaining Trust and Relationships Analyzing Customer Needs Managing Suppliers and Partners Customer Journey Step 3: Offer Purpose of the Module Purpose of Shaping Demand and Service Offerings Module Topics Managing Demand and Opportunities Specifying and Managing Customer Requirements Designing Service Offerings and User Experience Selling and Obtaining Service Offerings Customer Journey Step 4: Agree Purpose of the Module Purpose of Aligning Expectations and Agreeing on Services Module Topics Agreeing on and Planning Value Co-Creation Negotiating and Agreeing on a Service Customer Journey Step 5: Onboard Purpose of the Module Purpose of Onboarding and Offboarding ITIL® Management Practices Module Topics Planning Onboarding Fostering Relationships with Users Providing User Engagement and Delivery Channels Enabling Users for Service Elevating Mutual Capabilities Offboarding Customer Journey Step 6: Co-create Purpose of the Module Purpose of Service Provision and Consumption Module Topics Service Mindset Ongoing Service Interactions Nurturing User Communities Customer Journey Step 7: Realize Purpose of the Module Measuring Service Value Purpose of Value Capturing and Customer Journey Improvement Realizing Service Value in Different Settings Module Topics Tracking Value Realization Assessing and Reporting Value Realization Evaluating Value Realization and Improving Customer Journeys Realizing Value for the Service Provider

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Duration 3 Days 18 CPD hours This course is intended for This course is intended for IT professionals who need to manage the day-to-day environment of an SCCM 2012 SP1 or newer environment. Knowledge of the workings of a standalone primary SCCM site and basic PowerShell experience is recommended. Overview Create additional site system roles on existing or new servers. Modify high level site settings. Create and modify Discovery Methods, Boundaries and Boundary Groups. Create Collections using any of the membership rules available. Delegate authority through Roles and Scopes. Install the Configuration Manager client, modify client settings and restrict access to site systems. Deploy software to clients. Deploy software updates to clients. Configure compliance settings targeted against collections. Modify settings that govern monitoring functions such as Alerts and Status Settings. Work with Task Sequences for Operating System Deployment. Write basic PowerShell scripts using cmdlets learned and scripting constructs to accomplish configuration tasks. This course provides students with the knowledge and skills needed to use PowerShell for System Center Configuration Manager (SCCM) administration. In this course, students learn how to access the PowerShell cmdlets included with SCCM 2012 R2 and use them to perform configuration tasks for a primary site. Individual cmdlets will be used in working with objects such as Boundaries, Boundary Groups, Collections, Software Deployment, Patching, Compliance Settings, OSD Task Sequences, and many others. Basic scripting will also be covered so that students can learn how to put PowerShell to use when working with large sets of objects. Prerequisites Basic Windows and Active Directory knowledge. Conceptual knowledge of Configuration Manager objects and how they interact. Basic experience performing configuration tasks in ECM using the graphical console. Experience working from a command prompt. Basic knowledge of the fundamentals of Windows PowerShell. 1 - REVIEW OF SYSTEM CENTER CONFIGURATION MANAGER CONCEPTS Architecture of an System Center 2012 Configuration Manager Installation Managing Assets Content Delivery and Management Security, Monitoring, and Remote Management 2 - MANAGING RESOURCES Implementing Discovery Organizing Resources with Collections Working with Boundaries 3 - WORKING WITH CLIENTS Installing the Configuration Manager Client Managing Client Settings Managing Client Operations Monitoring Client Status 4 - DISTRIBUTING SOFTWARE Configure the Software Distribution Components Working with Distribution Points Creating Content for Distribution Deploying Software Applications 5 - UPDATING SYSTEMS WITH WSUS AND SCCM Integrating Configuration Manager and WSUS Managing Updates through Software Update Groups Creating and Deploying Update Packages Working with Automatic Deployment Rules 6 - HOW POWERSHELL CAN MANAGE COMPLIANCE SETTINGS Creating Compliance Settings Objects Deploying and Monitor the Baseline 7 - CONFIGURING OPERATING SYSTEM DEPLOYMENT OBJECTS Preparing the OSD Environment Working with Task Sequences 8 - WORKING AT THE SITE LEVEL Modify the Site Adding Site System Roles Adding a Secondary Site 9 - SECURITY AND MONITORING Configuring Role Based Administration Implementing Endpoint Protection Configuring Monitoring Options 10 - USING POWERSHELL SCRIPTING TO AUTOMATE SCCM TASKS Review of Scripting Constructs Introduction to the Configuration Manager WMI Classes

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

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