5:30 午後 - 9:00 午後 (UTC)

Microsoft Reactor Student meetups are for students to engage, learn and connect with Microsoft Most Valued Professionals (MVP’s), Microsoft Student Ambassadors, Partners and Microsoft Team. It’s an opportunity for them to enhance there careers in technology and personal learning. Our regular student meetups are an opportunity to hear from fellow students, peers and leaders in the industry about new technologies and also a chance for the students to network with potential employers. Agenda: 6:00PM – Doors Open 6:30 PM – Welcome by Liam Hampton, Regional Cloud Advocate at Microsoft 6:40 PM – 7:00PM - Session 1 7:00PM – 7:20PM – Session 2 7:20PM – 7:30 – Break 7:30PM – 8:15 – Session 3

11:00 午前 - 12:00 午後 (UTC)

Calling all students interested in the intersection of technology and speech! Are you looking to gain new technical skills while exploring cutting-edge use cases for speech technology? Look no further than our upcoming workshop on getting started with Azure Speech Service! In this hands-on workshop, you'll get an intro to the Azure Speech Service, learn how to deploy it into an end-to-end solution and unlock the power of speech recognition and synthesis for a variety of applications. Whether you're interested in building speech-enabled chatbots, voice-activated home automation systems, or anything in between, this workshop will provide you with the technical foundation you need on Azure to get started. To make things more interesting -- we'll also be diving a little into some of the most exciting and innovative use cases for speech technology today! So join us for this unique opportunity to gain valuable technical skills, explore new use cases, and connect with other students who share your passion for technology and speech. We can't wait to see you there!

11:00 午前 - 12:00 午後 (UTC)

What is the Session About? The session is about exploring how Azure can be used to power data engineering and data science workflows. Specifically, the session will cover the core Azure services that enable data engineering and data science workloads, including Azure Data Factory, Azure Database, and Azure Machine Learning. The session is designed to be hands-on, with attendees being guided through the process of setting up and configuring data pipelines, building scalable data processing and analytics workflows, and building, training, and deploying machine learning models at scale using Azure. By the end of the session, attendees will have a solid understanding of how to use Azure to power their data engineering and data science workflows. Who is it aimed at? This session is aimed at enthusiastic students, data engineers, data scientists, and IT professionals who are interested in exploring data workloads & solutions in the cloud. No prior experience with Azure is required, but participants should have a basic understanding of Data & Machine Learning concepts Why should you attend? If you are a developer or a software engineer who is uncertain about how data engineering fits into machine learning & the cloud, this session is for you. It's common to view data engineering as a separate art that's practiced only by elite developers, but this session will help dispel those doubts. By attending, you'll learn how data engineering & machine learning can be integrated with azure and how they can be used to enhance decision making.

2:11 午後 - 4:11 午後 (UTC)

Why is everyone talking about AI today? We probably haven’t seen a similar media phenomenon since the birth of the Internet or the mobile phones launch. The reasons are multiple, but a common aspect among all those technological revolutions is their huge impact on all aspects of society. If you are struggling to keep up with the news and you are looking for some guidance to find your way in the labyrinth of AI domain language, we are here for you! This session aims to demystify Natural Language Processing and Generation fundamentals as well as to explore AI services on Azure.

2:00 午後 - 3:00 午後 (UTC)

In this session, we will explore how to use Azure DevOps Pipeline to deploy a sentinment analysis project. We will cover how to use Azure DevOps pipeline to create a CI/CD pipeline for the creation of Azure infrastructures using bicep, tag and push a docker image to Azure Container Registry and deploy Sentinment analysis app to Azure web apps for containers. By the end of the session, you will have hands-on experience with using the Azure DevOps  Pipelines to deploy a sentiment analysis application using.