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
Why Learn Sketchup and Stable Diffusion Rendering Course? Course Link SketchUp and Stable Diffusion Rendering Course. An AI image creation course designed to explore AI image creation techniques and master the use of advanced AI technology. You'll learn Ai 3D modeling, advanced rendering, and lighting techniques. Duration: 16 hrs. Method: 1-on-1 Online Over Zoom is also available. Schedule: Tailor your own schedule by pre-booking a convenient hour of your choice, available from Mon to Sat between 9 am and 7 pm. The Sketchup and Stable Diffusion Rendering Course equips students with comprehensive skills for visually stunning Ai (Artificial intelligence) 3D models and renderings. Master Sketchup's user-friendly interface, advanced rendering techniques, and stable diffusion rendering. Hands-on exercises and real-world projects enhance learning. Ideal for architecture, interior design, product development, and visualization careers. The Sketchup and Stable Diffusion Rendering Course equips students with comprehensive skills for visually stunning Ai (Artificial intelligence) 3D models and renderings. Master Sketchup's user-friendly interface, advanced rendering techniques, and stable diffusion rendering. Hands-on exercises and real-world projects enhance learning. Ideal for architecture, interior design, product development, and visualization careers. Sketchup and Stable Diffusion Rendering Course (16 hours) Module 1: Introduction to Sketchup (2 hours) Overview of Sketchup software and interface navigation Basic drawing tools and geometry creation techniques Module 2: Texturing and Materials (2 hours) Applying textures and customizing materials Exploring texture mapping and material libraries Module 3: Lighting and Shadows (2 hours) Understanding lighting principles and light placement Creating realistic shadows and reflections Module 4: Advanced Modeling Techniques (3 hours) Creating complex shapes and utilizing advanced tools Working with groups, components, and modifiers Module 5: Stable Diffusion Rendering (2 hours) Introduction to stable diffusion rendering Configuring rendering settings for optimal results Module 6: Scene Composition and Camera Setup (2 hours) Exploring composition principles and camera perspectives Managing scenes and creating walkthrough animations Module 7: Rendering Optimization (2 hours) Optimizing models for faster rendering Using render passes and post-processing techniques Module 8: Project Work and Portfolio Development (1 hour) Applying skills to complete a real-world project Showcasing work in a professional portfolio Optional: Installing Stable Diffusion and Python (Additional 10 hours) Module 1: Introduction to Stable Diffusion and Python Overview of Stable Diffusion and Python's significance Module 2: System Requirements Hardware and software prerequisites for installation Module 3: Installing Python Step-by-step installation process for different OS Module 4: Configuring Python Environment Setting up environment variables and package managers Module 5: Installing Stable Diffusion Downloading and installing the Stable Diffusion package Module 6: Setting Up Development Environment Configuring IDEs for Python and Stable Diffusion Module 7: Troubleshooting and Common Issues Identifying and resolving common installation errors Module 8: Best Practices and Recommendations Managing Python and Stable Diffusion installations Module 9: Practical Examples and Projects Hands-on exercises demonstrating usage of Stable Diffusion and Python Module 10: Advanced Topics (Optional) Exploring advanced features and techniques Stable Diffusion UI v2 | A simple 1-click way to install and use https://stable-diffusion-ui.github.io A simple 1-click way to install and use Stable Diffusion on your own computer. ... Get started by downloading the software and running the simple installer. Learning Outcomes: Upon completing the Sketchup and Stable Diffusion Rendering Course, with a focus on AI image rendering, participants will: Master AI Image Rendering: Gain expertise in using AI-powered rendering techniques to create realistic and high-quality visualizations. Utilize Sketchup for 3D Modeling: Navigate the software, proficiently use drawing tools, and create detailed 3D models. Optimize Renderings: Apply AI-based rendering to optimize model visuals, achieving faster rendering times and superior image quality. Implement AI-driven Lighting and Shadows: Utilize AI algorithms for lighting placement, shadows, and reflections, enhancing realism in renderings. Create Professional Portfolio: Showcase AI-rendered projects in a professional portfolio, highlighting advanced image rendering skills. Note: The course focuses on AI image rendering using Sketchup and Stable Diffusion techniques, empowering participants with cutting-edge skills for creating exceptional visual representations.
Whetstone Communications and comms2point0 are pleased to bring you the Data Bites series of free webinars. Our aim is to boost interest and levels of data literacy among not-for-profit communicators.
This Level 4 course aims to equip professionals with the knowledge about the skills and practical behaviours which are required for them to step into a leadership/management role. The demand for management roles is expected to grow in the coming years. This is due to a number of factors, including: The ageing population, which is leading to a shortage of skilled workers. The increasing complexity of businesses requires more managers to oversee operations. The growing importance of technology is creating new opportunities for managers to lead and innovate.
Who is this course for? Sketchup Artificial Intelligence Training Course. Mastering SketchUp Artificial Intelligence (AI) is essential for designers, offering automation, efficiency, and innovative solutions. It saves time, enhances visualizations, fosters collaboration, and future-proofs skills, ensuring a competitive edge in the design industry. Click here for more info: Website How to Book? 1-on-1 training. Customize your schedule from Mon to Sat from 9 am to 7 pm Call to book Duration: 16 hours. Method: In-person or Live Online Sketchup and (Artificial Intelligence) Stable Diffusion Rendering Course (16 hours) Module 1: Sketchup Fundamentals (2 hours) Sketchup software overview and interface navigation Introduction to basic drawing tools and fundamental geometry creation techniques Module 2: Texturing and Material Mastery (2 hours) Application of textures and customization of materials Exploration of texture mapping and comprehensive material libraries Module 3: Illumination and Shadows (2 hours) Comprehending lighting principles and strategic light placement Crafting realistic shadows and reflections Module 4: Advanced Modeling Techniques (3 hours) Creating intricate shapes and harnessing advanced modeling tools Efficiently managing groups, components, and modifiers Module 5: Stable Diffusion Rendering (2 hours) Initiating stable diffusion rendering Optimizing rendering settings for superior outcomes Module 6: Scene Composition and Camera Configuration (2 hours) Exploring composition principles and camera perspectives Scene management and creation of captivating walkthrough animations Module 7: Rendering Optimization Strategies (2 hours) Techniques for optimizing models to expedite rendering Application of render passes and post-processing methods Module 8: Real-World Projects and Portfolio Building (1 hour) Application of acquired skills in completing authentic projects Professional portfolio presentation techniques Optional: Stable Diffusion and Python Installation (Additional 10 hours) Module 1: Introduction to Stable Diffusion and Python Comprehensive understanding of Stable Diffusion and Python's significance Module 2: System Prerequisites Hardware and software requirements for successful installation Module 3: Python Installation Guide Step-by-step installation process for various operating systems Module 4: Configuring Python Environment Configuration of environment variables and package managers Module 5: Stable Diffusion Installation Downloading and installing the Stable Diffusion package Module 6: Setting Up the Development Environment Configuration of integrated development environments (IDEs) for Python and Stable Diffusion Module 7: Troubleshooting and Common Issues Identification and resolution of common installation errors Module 8: Best Practices and Recommendations Effective management of Python and Stable Diffusion installations Module 9: Practical Applications and Projects Hands-on exercises exemplifying the practical usage of Stable Diffusion and Python Module 10: Advanced Topics (Optional) Exploration of advanced features and techniques Stable Diffusion https://stablediffusionweb.com https://stable-diffusion-ui.github.io https://stability.ai/stable-diffusion Upon successful completion of the Sketchup and Stable Diffusion Rendering Course with a focus on AI image rendering, participants will achieve the following: 1. Mastery of AI Image Rendering: Attain expertise in employing AI-powered rendering techniques to produce realistic and top-quality visualizations. 2. Proficiency in Sketchup for 3D Modeling: Navigate the software adeptly, utilize drawing tools with proficiency, and craft intricate 3D models. 3. Enhanced Rendering Optimization: Implement AI-based rendering to enhance model visuals, resulting in faster rendering times and superior image quality. 4. Application of AI-driven Lighting and Shadows: Employ AI algorithms for precise lighting placement, shadows, and reflections, elevating the realism of renderings. 5. Development of a Professional Portfolio: Present AI-rendered projects within a polished professional portfolio, highlighting advanced image rendering capabilities. 1. Mastering Sketchup: Attain proficiency in Sketchup, a renowned and user-friendly 3D modeling software, equipping you with the skills needed to adeptly create and manipulate 3D models. 2. Advanced Rendering Expertise: Explore stable diffusion rendering, an avant-garde technique that simplifies the creation of realistic and high-quality renderings. Broaden your rendering capabilities, producing visually stunning representations of your designs. 3. Practical Industry Applications: Cultivate practical skills relevant to diverse industries, encompassing architecture, interior design, product development, and visualization. Elevate your professional portfolio with captivating renderings that showcase your design prowess. 4. Interactive Learning: Participate in hands-on exercises and projects that promote active learning and the practical application of concepts. Benefit from personalized feedback and expert guidance, ensuring your continuous progress throughout the course. 5. Career Advancement: Elevate your career prospects by adding valuable skills to your toolkit. Proficiency in crafting detailed 3D models and impressive renderings through stable diffusion techniques opens doors to diverse job opportunities within the design and visualization sector. 6. Flexibility and Convenience: Access course materials online and learn at your own pace. Enjoy the flexibility of tailoring the coursework to your schedule, allowing you to harmonize your learning journey with other commitments. Course Advantages: Tailored Learning: Enjoy personalized 1-on-1 sessions, accommodating your schedule from Monday to Saturday, 9 am to 7 pm. Mastery of Sketchup: Develop proficiency in the widely-used and user-friendly 3D modeling software, enabling efficient creation and manipulation of 3D models. Advanced Rendering Proficiency: Acquire expertise in stable diffusion rendering for producing realistic, high-quality renderings that enhance the visual appeal of your designs. Practical Applicability: Develop practical skills applicable across diverse domains, including architecture, interior design, product development, and visualization, enriching your professional portfolio. Interactive Practical Experience: Engage in hands-on exercises with personalized guidance from seasoned instructors, ensuring consistent progress in your skillset. Career Progression: Boost your career opportunities by gaining valuable skills in 3D modeling and generating impressive renderings through stable diffusion techniques. Comprehensive Support: Benefit from free portfolio reviews, mock interviews, and career advice, providing additional resources to enhance your professional journey.
This practitioner-level 4 award encourages individuals in IT and technical roles to explore the many teams, ideas, and functions within an organisation and maximise their contribution. You will achieve this by learning the key concepts and considering behaviour and response in different scenarios.
This Level 4 practitioner award encourages individuals in or working towards a leadership role (this could be an IT or technical based-role), and you want to demonstrate modern leadership behaviours to nurture a high-performing team, especially during a time of organisational change.
Duration 5 Days 30 CPD hours This course is intended for A Microsoft Power Platform Functional Consultant is responsible for creating and configuring apps, automations, and solutions. They act as the liaison between users and the implementation team. The functional consultant promotes utilization of solutions within an organization. The functional consultant may perform discovery, engage subject matter experts and stakeholders, capture requirements, and map requirements to features. They implement components of a solution including application enhancements, custom user experiences, system integrations, data conversions, custom process automation, and simple visualizations. This course will teach you to use Microsoft Power Platform solutions to simplify, automate, and empower business processes for organizations in the role of a Functional Consultant. A Microsoft Power Platform Functional Consultant is responsible for creating and configuring apps, automations, and solutions. They act as the liaison between users and the implementation team. The functional consultant promotes utilization of solutions within an organization. The functional consultant may perform discovery, engage subject matter experts and stakeholders, capture requirements, and map requirements to features. They implement components of a solution including application enhancements, custom user experiences, system integrations, data conversions, custom process automation, and simple visualizations. This course may contain a 1-day Applied Workshop. This workshop will allow you to practice your Functional Consultant skills by creating an end-to-end solution to solve a problem for a fictitious company. The solution will include a Microsoft Dataverse database, Power Apps canvas app, and Power Automate flows. Prerequisites Experience as an IT professional or student Working knowledge of Microsoft Power Platform and its key components Knowledge of Microsoft Dataverse (or general data modeling) and security concepts 1 - Describe the business value of the Microsoft Power Platform Explore Microsoft Power Platform Describe the business value of the Power Platform Explore connectors and Microsoft Dataverse Describe how Power Platform works with Microsoft 365 apps and services Explore how Power Platform works with Microsoft Teams Describe how Power Platform works with Microsoft Dynamics 365 apps Describe how Power Platform solutions consume Microsoft Azure services Explore how Microsoft Power Platform apps work together Use Artificial Intelligence to increase productivity 2 - Core components of Power Pages Get started with Power Pages Core tools and components of Power Pages Overview of Power Pages security Overview of Power Pages extensibility 3 - Explore Power Pages templates Site design templates Scenario-based templates Dynamics 365 Power Pages site templates 4 - Explore Power Pages design studio Work with pages Page components Site styling and templates 5 - Explore Power Pages design studio data and security features Data workspace in Power Pages design studio Power Pages security features 6 - Introduction to Power Pages administration Power Pages administrative tools Set up workspace in Power Pages design studio 7 - Get started building with Power BI Use Power BI Building blocks of Power BI Tour and use the Power BI service 8 - Get data with Power BI Desktop Overview of Power BI Desktop Explore Power BI Desktop Connect to data sources Get data from Excel Transform data to include in a report Combine data from multiple sources Clean data to include in a report 9 - Model data in Power BI How to manage your data relationships Create calculated columns Optimize data models Create measures Create calculated tables Explore time-based data 10 - Use visuals in Power BI Create and customize simple visualizations Create slicers Map visualizations Matrices and tables Create scatter, waterfall, and funnel charts Modify colors in charts and visuals Page layout and formatting 11 - Explore data in Power BI Quick insights in Power BI Create and configure a dashboard Ask questions of your data with natural language Create custom Q&A suggestions Share dashboards with your organization Display visuals and tiles in full screen Edit tile details and add widgets Get more space on your dashboard 12 - Publish and share in Power BI Publish Power BI Desktop reports Print and export dashboards and reports Introducing Power BI Mobile Create workspaces in Power BI Build apps Use apps Integrate OneDrive for Business with Power BI Publish to web 13 - Create and manage workspaces in Power BI Distribute a report or dashboard Monitor usage and performance Recommend a development life cycle strategy Troubleshoot data by viewing its lineage Configure data protection 14 - Manage semantic models in Power BI Use a Power BI gateway to connect to on-premises data sources Configure a semantic model scheduled refresh Configure incremental refresh settings Manage and promote semantic models Troubleshoot service connectivity Boost performance with query caching (Premium) 15 - Create dashboards in Power BI Configure data alerts Explore data by asking questions Review Quick insights Add a dashboard theme Pin a live report page to a dashboard Configure a real-time dashboard Set mobile view 16 - Implement row-level security Configure row-level security with the static method Configure row-level security with the dynamic method 17 - Create tables in Dataverse Table characteristics Table relationships Dataverse logic and security Dataverse auditing Dual-write vs. virtual tables 18 - Manage tables in Dataverse Identify tables and table types in Dataverse Create a custom table Enable attachments within a table Licensing requirements for each table type 19 - Create and manage columns within a table in Dataverse Define columns in Microsoft Dataverse Column types in Microsoft Dataverse Add a column to a table Create a primary name column Restrictions that apply to columns in a table Create an auto numbering column Create an alternate key 20 - Create a relationship between tables in Dataverse Relate one or more tables - Introduction Relationship types that are available in Microsoft Dataverse Create a one-to-many relationship between tables Create a many-to-many relationship between tables Edit or delete relationships 21 - Working with choices in Dataverse Define choice column Standard choices column 22 - Get started with security roles in Dataverse Understand environment roles Adding or disabling an environment user Understand security concepts in Dataverse Understand user security roles and security role defaults Check the roles that a user belongs to Configure Dataverse teams for security Configure Dataverse group teams for security 23 - Use administration options for Dataverse Use Microsoft Power Platform Admin Center portal Tenant storage capacity Advanced Customization options in Power Apps Portal Enable and disable auditing 24 - Manage Dynamics 365 model-driven app settings and security Configure role-based security Manage teams and business units Explore settings and customizations 25 - Introduction to Microsoft Power Platform security and governance Identify Microsoft Power Platform environments Data Loss Prevention policies Microsoft Power Platform Center of Excellence Starter Kit 26 - Get started with model-driven apps in Power Apps Introducing model-driven apps Components of model-driven apps Design model-driven apps Incorporate business process flows 27 - Configure forms, charts, and dashboards in model-driven apps Forms overview Form elements Configure multiple forms Use specialized form components Configure views overview Configure grids Create and edit views Configure charts overview Dashboards overview Use interactive streams and tiles 28 - Get started with Power Apps canvas apps Power Apps building blocks Ways to build Power Apps Power Apps related technologies Additional Power Apps related technologies Designing a Power Apps app 29 - Connect to other data in a Power Apps canvas app Overview of the different data sources Work with action-based data sources Power Automate is a companion to Power Apps 30 - How to build the UI in a canvas app in Power Apps Use themes to quickly change the appearance of your app Branding a control Icons Images Personalization Using the tablet or phone form factors 31 - Manage apps in Power Apps Power Apps review 32 - Build your first app with Power Apps and Dataverse for Teams Create your first app with the hero template Customize your app with Power Apps Studio Publish your app Install template apps 33 - Access Dataverse in Power Pages websites Use lists to display multiple Dataverse records Use forms to interact with Dataverse data 34 - Authentication and user management in Power Pages Power Pages authentication settings User registration in Power Pages Authentication management for Power Pages users Power Pages authentication providers 35 - Power Pages maintenance and troubleshooting Power Pages website maintenance Power Pages website troubleshooting 36 - Define and create business rules in Dataverse Define business rules - Introduction Define the components of a business rule Create a business rule 37 - Get started with Power Automate Introducing Power Automate Troubleshoot flows 38 - Use the Admin center to manage environments and data policies in Power Automate Administer flows Export and import flows Learn how to distribute button flows 39 - Use Dataverse triggers and actions in Power Automate Dataverse triggers Query data Create, update, delete, and relate actions 40 - Extend Dataverse with Power Automate Set up a flow and configure its trigger Email Dataverse record Add to-do items Test and run your flow 41 - Introduction to expressions in Power Automate Get started with expressions Notes make things easier Types of functions Write complex expressions 42 - Build your first Power Automate for desktop flow Set up the environment Explore Power Automate for desktop Create your first Power Automate for desktop flow Record Power Automate for desktop actions Edit and test recorded actions 43 - Run a Power Automate for desktop flow in unattended mode Set up an unattended desktop flow Create a new cloud flow that calls an existing flow in unattended mode Perform a test run Best practices 44 - Optimize your business process with process advisor Get familiar with process advisor Create your first recording Edit recordings and group actions Analyze recordings and interpret results Automation recommendations 45 - Get started with Microsoft Copilot Studio bots Get started working with environments Create bots and work with the Microsoft Copilot Studio interface Create topics Test bots Publish bots and analyze performance 46 - Enhance Microsoft Copilot Studio bots Use Power Automate to add actions Transfer conversations to agents by using Omnichannel for Customer Service Create topics for existing support content Analyze bot performance 47 - Manage topics in Microsoft Copilot Studio Work with bot topics Branch a topic Create topics for existing support content Work with system fallback topics Manage topics 48 - Manage Power Virtual Agents Environments in Microsoft Copilot Studio Bot topics permissions Bot entities and flow permissions Monitor and diagnose Administer and manage Export and import bots Authentication 49 - Get started building with Power BI Use Power BI Building blocks of Power BI Tour and use the Power BI service 50 - Get data with Power BI Desktop Overview of Power BI Desktop Explore Power BI Desktop Connect to data sources Get data from Excel Transform data to include in a report Combine data from multiple sources Clean data to include in a report 51 - Model data in Power BI How to manage your data relationships Create calculated columns Optimize data models Create measures Create calculated tables Explore time-based data 52 - Use visuals in Power BI Create and customize simple visualizations Create slicers Map visualizations Matrices and tables Create scatter, waterfall, and funnel charts Modify colors in charts and visuals Page layout and formatting 53 - Explore data in Power BI Quick insights in Power BI Create and configure a dashboard Ask questions of your data with natural language Create custom Q&A suggestions Share dashboards with your organization Display visuals and tiles in full screen Edit tile details and add widgets Get more space on your dashboard 54 - Publish and share in Power BI Publish Power BI Desktop reports Print and export dashboards and reports Introducing Power BI Mobile Create workspaces in Power BI Build apps Use apps Integrate OneDrive for Business with Power BI Publish to web 55 - Manage solutions in Power Apps and Power Automate Add and remove apps, flows, and entities in a solution Edit a solution-aware app, flow, and table Build and deploy a complex solution with flows, apps, and entities Automate solution management 56 - Load/export data and create data views in Dataverse View data in a table Create or edit views of data in a table Load data into a table Export data from a table Add, update, or delete data in a table by using Excel Import data using Power Query Generate a new dataflow from an Excel Template Dataflow and Azure integration 57 - Get started with AI Builder Choose an AI capability Create your first model Ways to use your models 58 - Manage models in AI Builder Model lifecycle Manage model versions Share your models 59 - Use AI Builder in Power Automate AI Builder in Power Automate saves time Advanced usage of AI Builder in Power Automate 60 - Functional Consultant skills Create entity relationship diagrams Create and document mock-ups Document functional requirements and artifacts Complete fit-gap analysis Discuss stakeholder management responsibilities Understand industry accelerators Define Application Lifecycle Management Participate in testing Evaluate options Define connectors Understand Power Apps component framework 61 - Solution Architect series: Plan application lifecycle management for Power Platform Key considerations for ALM Solutions Configuration and reference data Release process ALM with Azure DevOps