Lewis Prince
Senior AI Engineer at Purple Frog Systems
Telford, United Kingdom
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Senior AI Engineer and international speaker, Lewis Prince specializes in building scalable AI solutions and predictive models that deliver real-world impact. He is known for his ability to simplify complex AI concepts and inspire organizations to innovate with confidence.
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Machine Learning in PowerBI
I will go through the machine learning and AI capabilities of PowerBi to show how we can further extract data, make data from data and most accurately infer for the future. I will delve into the pros and cons of using these tools through Power Bi and offer alternatives within the Microsoft Azure estate which specialize in certain tasks and also offer no to low code solutions.
AI Beyond the Hype; Practical Solutions for Real Businesses
AI is often associated with ChatGPT, self-driving cars, or highly complex research projects, which can make it feel distant or irrelevant to everyday business problems. This session breaks down those misconceptions and shows how AI is already accessible, practical, and valuable across almost every sector.
Through a series of clear, approachable demonstrations, attendees will see how different types of AI solutions can be applied to real business scenarios. We will showcase natural language processing, chatbots, and predictive models, using Azure AI Services, Copilot Studio, and Azure AutoML to demonstrate how these capabilities can be built and deployed without needing deep data science expertise.
Alongside the demos, the session explores real-world use cases across multiple industries, including Manufacturing, Retail, Leisure, Education, and Security, highlighting how similar AI techniques can solve very different problems. The focus is on understanding what each type of AI is good at, when it makes sense to use it, and how to choose the right tool for the job.
This session is aimed at data and technology professionals who want to move beyond hype and gain a clearer, more grounded understanding of how AI can deliver tangible value in real organisations.
By attending this session, you will learn how to distinguish between different types of AI solutions and their practical uses, understand how Azure AI Services, Copilot Studio, and Azure AutoML fit into the Microsoft AI ecosystem, see working demonstrations of NLP, chatbots, and predictive models, recognise where AI can add value across different industries, and gain confidence discussing and evaluating AI opportunities within your own organisation.
Automating Multilingual Document Translation with Microsoft Fabric and Azure AI
Modern organisations are increasingly multinational, producing large volumes of documents, such as reports, manuals, and communications, that are stored in Microsoft Fabric Lakehouses. Making this content accessible in multiple languages is a common challenge and is often handled manually or inconsistently.
This session shows how Azure AI Language Studio Translation APIs can be used to automate document translation directly from Fabric, enabling scalable and consistent multilingual access. We will cover the core concepts behind AI driven translation, why it makes sense as part of a data platform, and how it fits alongside other Azure AI services.
A live demonstration will walk through a practical, end to end implementation using Fabric pipelines and notebooks to orchestrate document translation from a Lakehouse via the Azure AI Translation APIs. Design decisions, integration patterns, and governance considerations will be explained along the way.
By attending this session, you will:
-Understand what Azure AI Language Studio offers and when to use translation services
-See how Microsoft Fabric can orchestrate AI services as part of a wider data platform
-Learn practical patterns for integrating AI into real data workflows
-Leave with approaches that can be reused beyond translation for other AI solutions
This session is aimed at data professionals who want to understand how to embed AI capabilities into practical, production-ready data platforms using Microsoft Fabric.
Responsible AI in Practice for the Microsoft Data Platform
As AI becomes embedded across the Microsoft Data Platform, from Copilot and Azure AI services to Microsoft Fabric, ethical considerations are now a practical responsibility for data professionals rather than a theoretical discussion. Decisions made during data preparation, modelling, and deployment directly affect fairness, transparency, and trust.
This session breaks down what AI ethics means in day-to-day data work and translates high-level principles into practical guidance for building AI-powered solutions on Azure and Fabric. It explores how issues such as bias, accountability, transparency, and privacy can emerge in real projects, often unintentionally, and how they can be addressed early in the solution lifecycle.
Using concrete examples, the session covers how bias can enter data models, governance considerations for AI features in Fabric and Power BI, and what Microsoft’s Responsible AI Standard means in practice when designing and deploying solutions. The focus is on helping attendees recognise ethical risks, ask the right questions, and make informed design choices.
By attending this session, you will:
-Learn how ethical risks arise in real-world data and AI solutions
-How bias can be introduced through data, modelling, and automation
-How to apply governance to AI features in Fabric and Power BI
-How Microsoft’s Responsible AI principles apply to real projects
-How to use a clear, actionable framework for evaluating AI features responsibly.
This session is aimed at data professionals who want to build AI solutions that are not only effective, but trustworthy, explainable, and aligned with real-world responsibilities.
Demystifying AutoML; Building Machine Learning Models with Azure
This session introduces Machine Learning from first principles, explaining the core concepts in a clear and accessible way. It clarifies how Machine Learning relates to Artificial Intelligence, showing how it is a branch of AI with a distinct purpose and approach, helping attendees understand where each fits.
The focus then moves to AutoML, exploring what is actually being automated across the machine learning lifecycle and why this is valuable for both newcomers and experienced practitioners. Realistic examples are used to demonstrate the types of problems that can be solved using Azure AutoML.
The session is built around three demonstrations. The first provides a guided tour of Azure Machine Learning Studio. The second shows how to create an AutoML model end to end, from data ingestion through training and deployment as a web service, with a brief coded example in VS Code using the Azure ML extension to show a faster, code-first approach. The final demo demonstrates how to consume predictions from the deployed model using a simple Excel and VBA interface, making machine learning outputs accessible through a familiar tool.
This session is aimed at data professionals who want a practical understanding of what machine learning and AutoML are, how they work, and how they can be applied using the Azure platform.
By attending this session, you will understand the difference between AI and machine learning, learn what AutoML automates across the ML lifecycle, see how to build and deploy AutoML models in Azure, and learn how to consume model predictions in tools such as Excel.
Unlocking Insight from Text Using Azure AI Language Studio
Organisations sit on vast amounts of textual data, such as customer feedback, reviews, and free-text comments, but extracting meaningful insight from that data is often slow and difficult. This session shows how Azure AI Language Studio can be used to analyse text quickly and at scale, turning unstructured text into actionable insight.
The session focuses on practical text analytics techniques, including key phrase extraction, sentiment analysis, and opinion mining. Using a real dataset of customer reviews, attendees will see how these AI capabilities can be applied to understand customer sentiment, identify common themes, and uncover what users are really saying.
Through live demonstrations, we will use Python to submit text data to the Azure AI Language Studio APIs, retrieve enriched results, and then feed those outputs into Power BI. The session concludes by visualising the analysed data in dashboards that break insights down by rating, location, and other dimensions, showing what a realistic end-to-end text analytics solution can look like.
This session is aimed at data professionals who want to understand how AI can be used to analyse unstructured text and integrate those insights into existing analytics and reporting platforms.
Using Microsoft Copilot Studio to Build Chatbots That Answer Questions and Take Action
This session demonstrates how powerful, task-driven chatbots can be created quickly using Microsoft’s Copilot Studio, with minimal technical effort. Attendees will see how chatbots can answer questions, automate actions, and integrate directly into everyday tools used across the organisation.
Through live demonstrations, we will build two chatbots based on different real-world use cases, using websites and SharePoint directories as knowledge sources. These bots will then be exposed instantly to Microsoft Teams, showing how conversational AI can be delivered to users without custom front-end development.
Beyond answering questions, the session shows how chatbots can be configured to perform actions, such as sending emails and writing data to spreadsheets. Alongside the demos, we will cover the core principles of effective chatbot design and discuss practical applications and benefits across a range of business scenarios.
By attending this session, you will learn how to design and build chatbots using existing content sources, how to deploy chatbots quickly into channels such as Microsoft Teams, how to enable chatbots to perform real actions like sending emails and updating spreadsheets, how these tools fit into the wider Copilot ecosystem, and how to identify use cases where conversational AI can deliver meaningful business value.
This session is aimed at data and technology professionals who want to understand how conversational AI can move beyond simple Q&A and become a practical, productivity-boosting tool within the Microsoft platform.
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Lewis Prince
Senior AI Engineer at Purple Frog Systems
Telford, United Kingdom
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