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Course Objectives At the end of this course you will be able to: Collaborate on documents Add reference marks and notes Make long documents easier to use Secure a document Work with forms '1 year email support service Take a closer look at the consistent excellent feedback from our growing corporate clients visiting our site ms-officetraining co uk With more than 20 years experience, we deliver courses on all levels of the Desktop version of Microsoft Office and Office 365; ranging from Beginner, Intermediate, Advanced to the VBA level. Our trainers are Microsoft certified professionals with a proven track record with several years experience in delivering public, one to one, tailored and bespoke courses. Tailored in company training courses: You can choose to run the course exactly as they are outlined by us or we can customise it so that it meets your specific needs. A tailored or bespoke course will follow the standard outline but may be adapted to your specific organisational needs. Collaborating on Documents Modify User Information Share a Document Compare Document Changes Review a Document Merge Document Changes Review Tracked Changes Coauthor Documents Adding Reference Marks and Notes Add Captions Add Cross-References Add Bookmarks Add Hyperlinks Insert Footnotes and Endnotes Add Citations and a Bibliography Simplifying and Managing Long Documents Insert Blank and Cover Pages Insert an Index Insert a Table of Contents Insert an Ancillary Table Manage Outlines Create a Master Document Securing a Document Suppress Information Set Formatting and Editing Restrictions Add a Digital Signature to a Document Restrict Document Access Forms Create Forms Manipulate Forms Who is this course for? Who is this course for? This course is designed for users who would like to create and work with lengthy and well structured documents, collaborate with others on documents, and create forms in Microsoft Word Requirements Requirements Preferably, delegates should have attended the Word Introduction course. Career path Career path Microsoft Office know-how can instantly increase your job prospects as well as your salary. 80 percent of job openings require spreadsheet and word-processing software skills

Duration 2 Days 12 CPD hours This course is intended for The primary audience for this course are persons who are new to reporting with Microsoft© SQL Server© Report Builder and SSRS, persons who are transitioning from another reporting software application, and persons who are existing Report Builder and SSRS report authors. Overview Navigate the Report Builder Environment. - Create table reports. - Format reports. - Create basic and complex expressions. - Group report data. - Create matrix reports. - Sort and filter data. - Summarize data with charts. - Print and export reports. In this course, students will continue their learning on the foundations of report writing with Microsoft© SQL Server© Report Builder and SSRS. Prerequisites ?Familiarity with Windows. ?Creating and navigating folders. ?Opening programs. ?Manipulating windows. ?Copying and pasting objects. ?Formatting text. ?Saving files. 1 - Exploring the Report Builder Environment Introducing the Report Builder Environment Working with Existing Reports Lab 1: Exploring the Report Builder Application 2 - Adding Data to Table Reports Create Report Data Sources Create Report Datasets Work with the Tablix Data Region Create a Table Report Lab 1: Creating Table Reports 3 - Formatting Data and Creating Expressions in Reports Formatting Reports Sorting and Filtering Report Data Adding Data to a Dataset Creating Simple Expressions Creating Complex Expressions Lab 1: Formatting Reports 4 - Grouping Report Data Group Data in Reports Group Data Using an Expression Creating Subgroups and Group Aggregates Lab 1: Creating Reports with Groups and Aggregates 5 - Matrix Reports Creating and Modifying Matrix Data Regions Creating and Modifying Column Groups Lab 1: Creating Matrix Reports 6 - Charts Create and Modify Chart Wizard Reports Add Charts to Existing Reports Modify Charts in Reports Lab 1: Creating Charts and Chart Reports 7 - Printing and Exporting Reports Print Features and Print Options Export Reports Lab 1: Printing and Exporting Reports

Duration 4 Days 24 CPD hours This course is intended for Software engineers concerned with building, managing and deploying AI solutions that leverage Azure AI Services, Azure AI Search, and Azure OpenAI. They are familiar with C# or Python and have knowledge on using REST-based APIs to build computer vision, language analysis, knowledge mining, intelligent search, and generative AI solutions on Azure. AI-102 Designing and Implementing an Azure AI Solution is intended for software developers wanting to build AI infused applications that leverage?Azure AI Services,?Azure AI Search, and?Azure OpenAI. The course will use C# or Python as the programming language. Prerequisites Before attending this course, students must have: Knowledge of Microsoft Azure and ability to navigate the Azure portal Knowledge of either C# or Python Familiarity with JSON and REST programming semantics Recommended course prerequisites AI-900T00: Microsoft Azure AI Fundamentals course 1 - Prepare to develop AI solutions on Azure Define artificial intelligence Understand AI-related terms Understand considerations for AI Engineers Understand considerations for responsible AI Understand capabilities of Azure Machine Learning Understand capabilities of Azure AI Services Understand capabilities of the Azure Bot Service Understand capabilities of Azure Cognitive Search 2 - Create and consume Azure AI services Provision an Azure AI services resource Identify endpoints and keys Use a REST API Use an SDK 3 - Secure Azure AI services Consider authentication Implement network security 4 - Monitor Azure AI services Monitor cost Create alerts View metrics Manage diagnostic logging 5 - Deploy Azure AI services in containers Understand containers Use Azure AI services containers 6 - Analyze images Provision an Azure AI Vision resource Analyze an image Generate a smart-cropped thumbnail 7 - Classify images Provision Azure resources for Azure AI Custom Vision Understand image classification Train an image classifier 8 - Detect, analyze, and recognize faces Identify options for face detection analysis and identification Understand considerations for face analysis Detect faces with the Azure AI Vision service Understand capabilities of the face service Compare and match detected faces Implement facial recognition 9 - Read Text in images and documents with the Azure AI Vision Service Explore Azure AI Vision options for reading text Use the Read API 10 - Analyze video Understand Azure Video Indexer capabilities Extract custom insights Use Video Analyzer widgets and APIs 11 - Analyze text with Azure AI Language Provision an Azure AI Language resource Detect language Extract key phrases Analyze sentiment Extract entities Extract linked entities 12 - Build a question answering solution Understand question answering Compare question answering to Azure AI Language understanding Create a knowledge base Implement multi-turn conversation Test and publish a knowledge base Use a knowledge base Improve question answering performance 13 - Build a conversational language understanding model Understand prebuilt capabilities of the Azure AI Language service Understand resources for building a conversational language understanding model Define intents, utterances, and entities Use patterns to differentiate similar utterances Use pre-built entity components Train, test, publish, and review a conversational language understanding model 14 - Create a custom text classification solution Understand types of classification projects Understand how to build text classification projects 15 - Create a custom named entity extraction solution Understand custom named entity recognition Label your data Train and evaluate your model 16 - Translate text with Azure AI Translator service Provision an Azure AI Translator resource Specify translation options Define custom translations 17 - Create speech-enabled apps with Azure AI services Provision an Azure resource for speech Use the Azure AI Speech to Text API Use the text to speech API Configure audio format and voices Use Speech Synthesis Markup Language 18 - Translate speech with the Azure AI Speech service Provision an Azure resource for speech translation Translate speech to text Synthesize translations 19 - Create an Azure AI Search solution Manage capacity Understand search components Understand the indexing process Search an index Apply filtering and sorting Enhance the index 20 - Create a custom skill for Azure AI Search Create a custom skill Add a custom skill to a skillset 21 - Create a knowledge store with Azure AI Search Define projections Define a knowledge store 22 - Plan an Azure AI Document Intelligence solution Understand AI Document Intelligence Plan Azure AI Document Intelligence resources Choose a model type 23 - Use prebuilt Azure AI Document Intelligence models Understand prebuilt models Use the General Document, Read, and Layout models Use financial, ID, and tax models 24 - Extract data from forms with Azure Document Intelligence What is Azure Document Intelligence? Get started with Azure Document Intelligence Train custom models Use Azure Document Intelligence models Use the Azure Document Intelligence Studio 25 - Get started with Azure OpenAI Service Access Azure OpenAI Service Use Azure OpenAI Studio Explore types of generative AI models Deploy generative AI models Use prompts to get completions from models Test models in Azure OpenAI Studio's playgrounds 26 - Build natural language solutions with Azure OpenAI Service Integrate Azure OpenAI into your app Use Azure OpenAI REST API Use Azure OpenAI SDK 27 - Apply prompt engineering with Azure OpenAI Service Understand prompt engineering Write more effective prompts Provide context to improve accuracy 28 - Generate code with Azure OpenAI Service Construct code from natural language Complete code and assist the development process Fix bugs and improve your code 29 - Generate images with Azure OpenAI Service What is DALL-E? Explore DALL-E in Azure OpenAI Studio Use the Azure OpenAI REST API to consume DALL-E models 30 - Use your own data with Azure OpenAI Service Understand how to use your own data Add your own data source Chat with your model using your own data 31 - Fundamentals of Responsible Generative AI Plan a responsible generative AI solution Identify potential harms Measure potential harms Mitigate potential harms Operate a responsible generative AI solution

Duration 1 Days 6 CPD hours This course is intended for This course is suitable for IT personnel who are just beginning to work with Azure. This audience wants to learn about our offerings and get hands-on experience with the product. This course primarily uses the Azure portal and command line interface to create resources and does not require scripting skills. Students in this course will gain confidence to take other role-based courses and certifications, such as Azure Administrator. This course combines lecture, demonstrations, and hands-on labs. This course will also help prepare someone for the AZ-900 exam. This course will provide foundational level knowledge on cloud concepts; core Azure services; and Azure management and governance features and tools. Prerequisites There are no prerequisites for taking this course. Familiarity with cloud computing is helpful, but isn't necessary. 1 - Describe cloud computing What is cloud computing Describe the shared responsibility model Define cloud models Describe the consumption-based model 2 - Describe the benefits of using cloud services Describe the benefits of high availability and scalability in the cloud Describe the benefits of reliability and predictability in the cloud Describe the benefits of security and governance in the cloud Describe the benefits of manageability in the cloud 3 - Describe cloud service types Describe Infrastructure as a Service Describe Platform as a Service Describe Software as a Service 4 - Describe the core architectural components of Azure What is Microsoft Azure Get started with Azure accounts Describe Azure physical infrastructure Describe Azure management infrastructure 5 - Describe Azure compute and networking services Describe Azure Virtual Machines Describe Azure Virtual Desktop Describe Azure Containers Describe Azure Functions Describe application hosting options Describe Azure Virtual Networking Describe Azure Virtual Private Networks Describe Azure ExpressRoute Describe Azure DNS 6 - Describe Azure storage services Describe Azure storage accounts Describe Azure storage redundancy Describe Azure storage services Identify Azure data migration options Identify Azure file movement options 7 - Describe Azure identity, access, and security Describe Azure directory services Describe Azure authentication methods Describe Azure external identities Describe Azure conditional access Describe Azure role-based access control Describe zero trust model Describe defense-in-depth Describe Microsoft Defender for Cloud 8 - Describe cost management in Azure Describe factors that can affect costs in Azure Compare the Pricing and Total Cost of Ownership calculators Describe the Microsoft Cost Management tool Describe the purpose of tags 9 - Describe features and tools in Azure for governance and compliance Describe the purpose of Microsoft Purview Describe the purpose of Azure Policy Describe the purpose of resource locks Describe the purpose of the Service Trust portal 10 - Describe features and tools for managing and deploying Azure resources Describe tools for interacting with Azure Describe the purpose of Azure Arc Describe Azure Resource Manager and Azure ARM templates 11 - Describe monitoring tools in Azure Describe the purpose of Azure Advisor Describe Azure Service Health Describe Azure Monitor Additional course details: Nexus Humans AZ-900T00 Microsoft Azure Fundamentals training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the AZ-900T00 Microsoft Azure Fundamentals course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Microsoft Excel® in Depth: In-House Training The goal of this course is to provide a deeper understanding of Excel and its intricacies and a new ability to use it efficiently producing the best solutions for your projects. This practical course provides a solid background of the features of Excel and a deeper understanding of its features, benefits and uses. This is not a beginner's course in Excel. You will learn some advanced features such as Pivot Tables, Charting, Tables, Sorting, Filtering and Functions. The goal of this course is to provide a deeper understanding of Excel and its intricacies and a new ability to use it efficiently producing the best solutions for your projects. What you Will Learn You'll learn how to: Use functions like IF, AVERAGE, SUMIF, SUMIFS, SUMPRODUCT, INDEX, MATCH, CHOOSE, DATE, and many more Create meaningful charts Use pivot tables Use Conditional Formatting, Data Validation Take advantage of using Named ranges, do sorting, filtering, tables Getting Started The building blocks of Excel, built-in functions, will be examined The basics of formatting your data will be examined Shortcuts and data manipulation will be explored Built-in features like those mentioned in the 'What you will learn' section above will be explored in detail Excel Functions - VLOOKUP, IF, INDEX, MATCH, CHOOSE, SUMIF, SUMIFS, SUMPRODUCT, DATE, so many more Using Named ranges, Data Validation, Sorting, and Filtering Learn the Name manager; Learn the difference between local and global names; Ensure correct access to linked workbooks; Ensure data accuracy; Learn how to use cascading data validation (for example, once a user chooses 'cars', another cell allows only Ford, Toyota, etc.); Sorting by more than 3 fields; Filtering by font, pattern, or value; See your data based on things like dates in the 3rd quarter, or fields where quantity x price is greater than some fixed value Conditional formatting and data formatting Make relevant data stand out Isolate highs and lows Make error cells invisible Learn about Data bars, Icon sets, and Color scales Highlight differences between worksheets Learn all the codes in the Format/Number list Using cell Styles Learn all about alignment, protection, borders, colors and more Pivot Tables Learn how to summarize large amounts of data with a few clicks Learn various ways of presenting the data Learn the various pivot table tools Learn how to customize and format a pivot table to suit your needs Learn how to group data Learn how to use the various options to present your data Charts Learn how to create a chart with one keystroke! Learn the 11 types of built-in charts Learn how to create a chart with one keystroke! Learn how to customize the charts to make the information tell the right story Learn how to use the design, layout, and formatting available to charts in Excel 2007 Learn embedded charts versus chart sheets Learn how to use modify all the pieces of a chart Array formulas Learn how to use the most powerful formulas in Excel Learn how to combine many formulas into one compact array-formula Learn the real power of these formulas and why regular formulas can't do the job Learn how to use built-in array formulas, like TREND or TRANSPOSE

Microsoft Excel® in Depth: Virtual In-House Training The goal of this course is to provide a deeper understanding of Excel and its intricacies and a new ability to use it efficiently producing the best solutions for your projects. This practical course provides a solid background of the features of Excel and a deeper understanding of its features, benefits and uses. This is not a beginner's course in Excel. You will learn some advanced features such as Pivot Tables, Charting, Tables, Sorting, Filtering and Functions. The goal of this course is to provide a deeper understanding of Excel and its intricacies and a new ability to use it efficiently producing the best solutions for your projects. What you Will Learn You'll learn how to: Use functions like IF, AVERAGE, SUMIF, SUMIFS, SUMPRODUCT, INDEX, MATCH, CHOOSE, DATE, and many more Create meaningful charts Use pivot tables Use Conditional Formatting, Data Validation Take advantage of using Named ranges, do sorting, filtering, tables Getting Started The building blocks of Excel, built-in functions, will be examined The basics of formatting your data will be examined Shortcuts and data manipulation will be explored Built-in features like those mentioned in the 'What you will learn' section above will be explored in detail Excel Functions - VLOOKUP, IF, INDEX, MATCH, CHOOSE, SUMIF, SUMIFS, SUMPRODUCT, DATE, so many more Using Named ranges, Data Validation, Sorting, and Filtering Learn the Name manager; Learn the difference between local and global names; Ensure correct access to linked workbooks; Ensure data accuracy; Learn how to use cascading data validation (for example, once a user chooses 'cars', another cell allows only Ford, Toyota, etc.); Sorting by more than 3 fields; Filtering by font, pattern, or value; See your data based on things like dates in the 3rd quarter, or fields where quantity x price is greater than some fixed value Conditional formatting and data formatting Make relevant data stand out Isolate highs and lows Make error cells invisible Learn about Data bars, Icon sets, and Color scales Highlight differences between worksheets Learn all the codes in the Format/Number list Using cell Styles Learn all about alignment, protection, borders, colors and more Pivot Tables Learn how to summarize large amounts of data with a few clicks Learn various ways of presenting the data Learn the various pivot table tools Learn how to customize and format a pivot table to suit your needs Learn how to group data Learn how to use the various options to present your data Charts Learn how to create a chart with one keystroke! Learn the 11 types of built-in charts Learn how to create a chart with one keystroke! Learn how to customize the charts to make the information tell the right story Learn how to use the design, layout, and formatting available to charts in Excel 2007 Learn embedded charts versus chart sheets Learn how to use modify all the pieces of a chart Array formulas Learn how to use the most powerful formulas in Excel Learn how to combine many formulas into one compact array-formula Learn the real power of these formulas and why regular formulas can't do the job Learn how to use built-in array formulas, like TREND or TRANSPOSE

This course will allow you to explore the potential of self-service business intelligence using Power BI Desktop to analyse and connect to different sources of data, creating Relationships between those different datasets, Query the data using Shaping and data Modelling, to create Visualizations, and publish Reports to different platforms . Course Objectives At the end of this course you will be able to: Connect to data from different sources. Use the Query Editor Perform Power BI desktop data Shaping and Transformation. Create Power BI desktop Modelling. Create Power BI desktop Visualizations and Reports. ' 1 year email support service Take a closer look at the consistent excellent feedback from our growing corporate clients visiting our site ms-officetraining co uk With more than 20 years experience, we deliver courses on all levels of the Desktop version of Microsoft Office and Office 365; ranging from Beginner, Intermediate, Advanced to the VBA level and Business Intelligence. Our trainers are Microsoft certified professionals with a proven track record with several years experience in delivering public, one to one, tailored and bespoke courses. Our competitive rates start from £550.00 per day of training Tailored training courses: You can choose to run the course exactly as they are outlined by us or we can customise it so that it meets your specific needs. A tailored or bespoke course will follow the standard outline but may be adapted to your specific organisational needs. Please visit our site (ms-officetraining co uk) to get a feel of the excellent feedback our courses have had and look at other courses you might be interested in. Introduction to Power BI Power BI Jargon explained A quick look at Power BI Desktop A quick look at the Power BI service Helpful resources Power BI and Excel Introduction to using Excel data in Power BI Upload Excel data to Power BI Import Power View and Power Pivot to Power BI Getting started with Power BI Desktop Overview of Power BI Desktop Accessing Help and Helpful resources Connect to data sources in Power BI Desktop Shaping and Transforming Data with Query Editor Introduction to the Query Editor Data Sources Power BI Desktop can Connect to Introduction to Steps and M code Combining Data Using Merge and Append Queries Data Type Properties Working with Delimiters Clean and transform your data with the Query Editor Text Specific Transformation Tools Number Specific Transformation Tools Date Specific Transformation Tools Split and Merge columns Creating an Index Column Adding Conditional Columns Columns From Examples Grouping and Aggregating data Pivoting and Unpivoting Using filters Modeling the data Introduction to modeling your data How to manage your data relationships Create calculated columns Optimizing data models Create calculated measures Show Values As and Quick Measures Create calculated tables Explore your time-based data Introduction to DAX DAX calculation types DAX functions Visualizations Introduction to visuals in Power BI Create and customize simple visualizations Modify colors in charts and visuals Shapes, text boxes, and images Page layout and formatting Group interactions among visualizations Visual hierarchies and drill-down Using custom visualizations Create a KPI Visualization Geo-Data and Maps Reports, Publishing and Sharing Introduction to the Power BI service 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 Introduction to content packs, security, and groups Publish Power BI Desktop reports Print and export dashboards and reports Create groups in Power BI Use content packs Update content packs Publish to web Who is this course for? Who is this course for? This course facilitates you with knowledge on the potential for Power BI Desktop to analyse and connect to different sources of data, creating Relationships between those different datasets, Query the data using Shaping and data Modelling, and to create Visualizations, and publish Reports to different platforms. Requirements Requirements Before attending this course, delegates should have: - A general knowledge of database concepts (fields, records and relationships) - Familiarity with Excel. Career path Career path Business Intelligence Data Analysis ETL & Data Warehousing

Duration 1 Days 6 CPD hours This course is intended for This course is designed for professionals in a variety of job roles who receive Power BI data visualizations and reports from data analysts or from data visualization engineers. These data report recipients want to use the features and capabilities of Power BI to fully explore the visualizations and initial analyses provided to them in reports, perform additional analysis to ask next-level questions of the data, and to customize and create new visualizations and dashboards in order to share new insights and create compelling reports. Overview Explore Power BI reports. Analyze data to get answers and insights. Sort and group data for analysis and reporting. Filter visualizations. Prepare reports. Troubleshoot, collaborate, and share reports. As data acquisition, access, analysis, and reporting are interwoven with our businesses and lives, more and more data is collected about business and personal activities. This abundance of data and the computing power to analyze it has increased the use of data analysis and data visualization across a broad range of job roles. Decision makers of all types, including managers and executives, must interact with, interpret, and develop reports based on data and analysis provided to them. Microsoft Power BI software is designed for data analysis and the creation of visualizations. Data analysts prepare data, perform initial analysis, and create visualizations that are then passed to business data decision makers. These decision makers can use Power BI's tools to explore the data, perform further analysis to find new insights, make decisions, and create customized reports to share their findings. Prerequisites To ensure your success in this course, you have experience managing data with Microsoft Excel or Google Sheets 1. Exploring Power BI Reports Topic A: Data Analysis Workflow with Power BI Topic B: Explore Reports in the Power BI Service Topic C: Edit Reports 2. Analyzing Data to Get Answers and Insights Topic A: Configure Data Visualizations Topic B: Ask New Questions by Changing Aggregation Topic C: Find Answers with Calculations 3. Sorting and Grouping Data for Analysis and Reporting Topic A: Sort Data Topic B: Group Data 4. Filtering Visualizations Topic A: Filter Data to Refine Analysis Topic B: Create Slicers for Reports 5. Preparing Reports Topic A: Format and Annotate Reports Topic B: Emphasize Data in Reports 6. Troubleshooting, Sharing, and Collaborating Topic A: Troubleshoot Data Issues Topic B: Collaborate in Power BI Topic C: Collaborate with Non-Power BI Users

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