115 Microsoft courses in Mansfield

This course is designed for those already using Power BI Desktop and are ready to work with more comprehensive elements of analysing and reporting in Power BI. The course maintains a balanced look at data analysis including the Power Query Editor, with a deep dive into writing DAX formulas, and enhanced dashboard visualisations. The aim of this course is to provide a more complete understanding of the whole Power BI analytics process, by working with business examples that will equip you with the necessary skills to output comprehensive reports and explore Power BI's analytical capabilities in more depth. 1 The Query Editor Grouping rows in a table Split row by delimiter Add days to determine deadlines The query editor 2 Fuzzy Matching Joins Matching inconsistencies by percentage Matching with transformation table 3 The Query Editor M Functions Adding custom columns Creating an IF function Nested AND logics in an IF function 4 DAX New Columns Functions Including TRUE with SWITCH Using multiple conditions The FIND DAX function The IF DAX function Logical functions IF, AND, OR 5 Editing DAX Measures Making DAX easier to read Add comments to a measure Using quick measures 6 The Anatomy of CALCULATE Understanding CALCULATE filters Add context to CALCULATE with FILTER Using CALCULATE with a threshold 7 The ALL Measure Anatomy of ALL Create an ALL measure Using ALL as a filter Use ALL for percentages 8 DAX Iterators Anatomy of iterators A closer look at SUMX Using RELATED with SUMX Create a RANKX RANKX with ALL 9 Date and Time Functions Overview of functions Create a DATEDIFF function 10 Time Intelligent Measures Compare historical monthly data Create a DATEADD measure Creating cumulative totals Creating cumulative measures Visualising cumulative totals 11 Visualisations In-Depth Utilising report themes Applying static filters Group data using lists Group numbers using bins Creating heatmaps Comparing proportions View trends with sparklines 12 Comparing Variables Visualising trendlines as KPI Forecasting with trendlines Creating a scatter plot Creating dynamic labels Customised visualisation tooltips Export reports to SharePoint

This course starts with data transformation strategies, exploring capabilities in the Power Query Editor, and data-cleansing practices. It looks at the Advanced Query Editor to view the M language code. This course focuses on advanced DAX measures that include filtering conditions, with a deep dive into time intelligence measures. Like the M query language, DAX is a rich functional language that supports variables and expression references. This course also looks at the creation of dynamic dashboards and incorporates a range of visualisations available in Power BI Desktop and online in the AppSource. The course finishes with a look at setting up end user level security in tables. 1 The query editor Split by row delimiter AddDays to determine deadlines Advanced query editor 2 Fuzzy matching joins Matching inconsistencies by percentage Matching with transformation table 3 Logical column functions Logical functions IF, AND, OR Using multiple conditions Including FIND in functions 4 Editing DAX measures Make DAX easier to read Add comments to a measure Using quick measures 5 The anatomy of CALCULATE Understanding CALCULATE context filters Adding context to CALCULATE with FILTER Using CALCULATE with a threshold 6 The ALL measure Anatomy of ALL Create an ALL measure Using ALL as a filter Use ALL for percentage 7 DAX iterators Anatomy of iterators A closer look at SUMX Using RELATED in SUMX Create a RANKX RANKX with ALL 8 Date and time functions Overview of functions Create a DATEDIFF function 9 Time intelligent measures Compare historical monthly data Create a DATEADD measure Creating cumulative totals Creating cumulative measures Visualising cumulative totals 10 Visualisations in-depth Utilising report themes Create a heatmap Comparing proportions View trends with sparklines Group numbers using bins Setting up a histogram 11 Comparing variables Visualising trendlines as KPI Forecasting with trendlines Creating a scatter plot Creating dynamic labels Customised visualisation tooltips Export reports to SharePoint 12 User level security Setting up row level security Testing user security

This course starts with the basics then moves seamlessly to an intermediate level. It includes a comprehensive yet balanced look at the four main components that make up Power BI Desktop: Report view, Data view, Model view, and the Power Query Editor. It also demonstrates how to use the online Power BI service. It looks at authoring tools that enables you to connect to and transform data from a variety of sources, allowing you to produce dynamic reports using a library of visualisations. Once you have those reports, the course looks at the seamless process of sharing those with your colleagues by publishing to the online Power BI service. The aim of this course is to provide a strong understanding of the Power BI analysis process, by working with real-world examples that will equip you with the necessary skills to start applying your knowledge straight away. 1 Getting started The Power BI process Launching Power BI Desktop The four views of Power BI Dashboard visuals 2 Connecting to files Connect to data sources Connect to an Excel file Connect to a CSV file Connect to a database Import vs. DirectQuery Connect to a web source Create a data table 3 Transforming data The process of cleaning data Column data types Remove rows with filters Add a custom column Append data to a table Fix error issues Basic maths operations 4 Build a data model Table relationships Manage table relationships 5 Merge queries Table join kinds Merging tables 6 Create report visualisations Creating map visuals Formatting maps Creating chart visuals Formatting chart Tables, matrixes, and cards Control formatting with themes Filter reports with slicers Reports for mobile devices Custom online visuals Export report data to Excel 7 The power query editor Fill data up and down Split columns by delimiter Add conditional columns Merging columns 8 The M formula Creating M functions Create an IF function Create a query group 9 Pivot and unpivot tables Pivot tables in the query editor Pivot and append tables Pivot but don't summarise Unpivot tables Append mismatched headers 10 Data modelling revisited Data model relationships Mark a calendar as a date table 11 Introduction to calculated columns New columns vs. measures Creating a new column calculation The SWITCH function 12 Introduction to DAX measures Common measure categories The SUM measure Adding measures to visuals COUNTROWS and DISINCTCOUNT functions DAX rules 13 The CALCULATE measure The syntax of CALCULATE Things of note about CALCULATE 14 The SUMX measure The SUMX measure X iterator functions Anatomy of SUMX 15 Introduction to time intelligence Importance of a calendar table A special lookup table The TOTALYTD measure Change year end in TOTALYTD 16 Hierarchy, groups and formatting Create a hierarchy to drill data Compare data in groups Add conditional formatting 17 Share reports on the web Publish to the BI online service Get quick insights Upload reports from BI service Exporting report data What is Q&A? Sharing your reports 18 Apply your learning Post training recap lesson

Course Duration: Half-day or full-day (can also be delivered as a 3-part virtual workshop series) Target Audience: Professionals in non-technical roles (e.g. executive assistants, HR, marketing, project managers, operations staff, trainers, and admin support) who want to use generative AI to enhance their work—without needing coding skills. Course Objectives By the end of this course, participants will be able to: Understand what generative AI is and how it works in plain language. Identify use cases relevant to their role or industry. Use popular generative AI tools (like ChatGPT, Gemini, and Copilot) confidently. Write effective prompts to get better, more relevant results. Apply AI ethically and responsibly in the workplace. Course Outline Module 1: Demystifying Generative AI What is generative AI? (Plain language explanation) How AI models like ChatGPT, Copilot, and Gemini work Examples of what generative AI can (and can’t) do Myths, risks, and benefits of AI in non-tech roles Module 2: Everyday Use Cases for Professionals Time-saving applications: Drafting emails, reports, meeting summaries Creating checklists, plans, or SOPs Enhancing creativity: Brainstorming ideas for events, campaigns, or training Writing social media posts, newsletters, or job ads Organising information: Summarising documents Structuring spreadsheets or creating templates Supporting communication: Improving tone and clarity Translating or simplifying content Module 3: Prompting Essentials What is a “prompt” and why does it matter? How to write clear, specific, and effective prompts Prompting frameworks (e.g., “Role–Task–Goal” method) Live practice: transforming a vague prompt into a powerful one Troubleshooting: when AI gives poor answers and how to improve them Module 4: Hands-On Exploration Try-it-yourself exercises using ChatGPT or Gemini (guided) Real workplace examples and team challenges Create an AI-generated email, checklist, or idea list Optional: use industry-specific examples (e.g., HR, admin, events, comms) Module 5: Responsible AI Use at Work Understanding AI limitations and biases Protecting privacy and sensitive data When not to use AI Workplace policies and guidelines (customisable for your organisation) Ethical use: attribution, transparency, and human review Module 6: Getting Started in Your Role Tools overview: free vs paid options (ChatGPT, Microsoft Copilot, Gemini) Building your own AI toolkit Tips for staying up to date as tools evolve 30-day challenge: how to build AI into your daily workflow Delivery Style Highly interactive, practical, and low-jargon No coding or tech background required Hands-on demos, guided practice, and scenario-based activities Group discussion and peer learning Course Materials Provided Quick-start guide: Top 10 prompts for non-tech roles AI Prompt Library for your job type Do’s and Don’ts for ethical use of AI at work “AI in Action” workbook with examples and checklists Personal AI Action Plan Optional Add-ons Team-based AI hackathon (mini workplace challenge) Tailored follow-up webinar for Q&A and deeper use cases Co-branded playbook for organisational AI use Integration with digital transformation or innovation initiatives

Course Duration: Half-day or full-day (can also be delivered as a 3-part virtual workshop series) Target Audience: Professionals in non-technical roles (e.g. executive assistants, HR, marketing, project managers, operations staff, trainers, and admin support) who want to use generative AI to enhance their work—without needing coding skills. Course Objectives By the end of this course, participants will be able to: Understand what generative AI is and how it works in plain language. Identify use cases relevant to their role or industry. Use popular generative AI tools (like ChatGPT, Gemini, and Copilot) confidently. Write effective prompts to get better, more relevant results. Apply AI ethically and responsibly in the workplace. Course Outline Module 1: Demystifying Generative AI What is generative AI? (Plain language explanation) How AI models like ChatGPT, Copilot, and Gemini work Examples of what generative AI can (and can’t) do Myths, risks, and benefits of AI in non-tech roles Module 2: Everyday Use Cases for Professionals Time-saving applications: Drafting emails, reports, meeting summaries Creating checklists, plans, or SOPs Enhancing creativity: Brainstorming ideas for events, campaigns, or training Writing social media posts, newsletters, or job ads Organising information: Summarising documents Structuring spreadsheets or creating templates Supporting communication: Improving tone and clarity Translating or simplifying content Module 3: Prompting Essentials What is a “prompt” and why does it matter? How to write clear, specific, and effective prompts Prompting frameworks (e.g., “Role–Task–Goal” method) Live practice: transforming a vague prompt into a powerful one Troubleshooting: when AI gives poor answers and how to improve them Module 4: Hands-On Exploration Try-it-yourself exercises using ChatGPT or Gemini (guided) Real workplace examples and team challenges Create an AI-generated email, checklist, or idea list Optional: use industry-specific examples (e.g., HR, admin, events, comms) Module 5: Responsible AI Use at Work Understanding AI limitations and biases Protecting privacy and sensitive data When not to use AI Workplace policies and guidelines (customisable for your organisation) Ethical use: attribution, transparency, and human review Module 6: Getting Started in Your Role Tools overview: free vs paid options (ChatGPT, Microsoft Copilot, Gemini) Building your own AI toolkit Tips for staying up to date as tools evolve 30-day challenge: how to build AI into your daily workflow Delivery Style Highly interactive, practical, and low-jargon No coding or tech background required Hands-on demos, guided practice, and scenario-based activities Group discussion and peer learning Course Materials Provided Quick-start guide: Top 10 prompts for non-tech roles AI Prompt Library for your job type Do’s and Don’ts for ethical use of AI at work “AI in Action” workbook with examples and checklists Personal AI Action Plan Optional Add-ons Team-based AI hackathon (mini workplace challenge) Tailored follow-up webinar for Q&A and deeper use cases Co-branded playbook for organisational AI use Integration with digital transformation or innovation initiatives