Improve your professional skills for this essential work
This blog highlights essential resources for driving technology adoption in organizations, focusing on practical skills and strategies. It introduces key video topics, including the role of a User Enablement Specialist, the importance of storytelling for engagement, a three-step approach to advancing tech careers, and vital presentation skills for gaining leadership support. Together, these resources offer actionable guidance for professionals seeking to champion digital transformation and foster successful adoption initiatives.Preparing for Your Organization’s AI Workloads – Student Learning Pathways
This structured plan helps students: Plans | Microsoft Learn Build foundational knowledge of AI in the cloud. Learn how enterprise-level infrastructure supports responsible, scalable AI deployments. Explore governance and monitoring strategies to ensure security and compliance. And the best part? It’s built using Microsoft’s existing training resources plus some brand-new modules to give you an edge. Your AI Readiness Journey on Azure 🎯 Milestone 1: Getting Started with AI on Azure https://learn.microsoft.com/training/paths/introduction-to-ai-on-azure/ Begin with the basics—from machine learning concepts to practical uses of Azure AI services. 🛡️ Milestone 2: Infrastructure Essentials https://learn.microsoft.com/training/paths/manage-iam-for-ai-workloads-on-azure/ https://learn.microsoft.com/training/paths/manage-network-access-ai-workloads/ Learn how enterprises secure access and manage identities—critical for real-world applications. 📊 Milestone 3: Monitoring AI Services https://learn.microsoft.com/training/paths/monitor-ai-workloads-on-azure/ Discover how businesses ensure their models perform safely and consistently at scale. 🏛️ Milestone 4: Advanced Management & Governance https://learn.microsoft.com/training/paths/ai-workloads-governance/ Master how organizations prevent data leaks and enforce responsible AI usage. 🆕 New Training Content Just for You To make this roadmap even more student-friendly, Microsoft has introduced updated and brand-new modules, including: Azure ML Authentication & Authorization Secure Azure AI Services Restrict Workspace Network Traffic Monitor Azure ML Prevent Data Exfiltration Govern AI Services with Azure Policy 🔗 Ready to Dive In? Whether you're exploring a career in AI or just getting started with Azure, these learning paths will level up your skills while helping you understand how real-world teams manage complex AI workloads. Start your journey on Microsoft Learn and become the architect of tomorrow’s intelligent systems. 💡 Would you like a version formatted for your internal newsletter or maybe something more conversational for social media? I can easily tailor it to fit the tone or medium you're aiming for.Azure OpenAI Training
Liebe Partner, unser Cloud Solution Architect Dennis Huyen hat ein vierteiliges Azure OpenAI Training für Sie erstellt. In dieser Trainingsreihe lernen Sie die wichtigsten Konzepte zu Generative AI und dem Azure OpenAI Service kennen. Außerdem erfahren Sie, wie Sie mithilfe der API und SDK von Azure OpenAI Service intelligente KI-Applikationen implementieren können. Im ersten Teil erhalten Sie eine Einführung zum Azure OpenAI Service und erhalten einen Überblick über verschiedene Anwendungsfälle In Teil 2 lernen Sie die wichtigsten Konzepte zu Generative AI, Prompting und Azure OpenAI kennen Teil 3 enthält eine Demo-Session, die Ihnen zeigt, wie Sie mithilfe des Azure OpenAI Studios und der API und SDK mit den Large Language Models von Azure OpenAI interagieren können Im vierten Teil präsentieren wir Ihnen, wie sie mithilfe von „Retrieval Augmented Generation“ und Embedding-Modellen intelligente KI-Applikationen entwickeln können Sehen Sie sich jetzt die Azure OpenAI Trainings an!How much does real-world practice matter compared to certifications when building skills?
Hi everyone, I’ve been spending time building skills through a mix of hands-on practice and certification preparation, and I’ve noticed there is often a gap between what exams test and what actually comes up in real scenarios. Certifications are useful for structure and validation, but in day-to-day work, troubleshooting, decision-making, and adapting to unexpected issues often seem just as important, sometimes even more. I’m interested in hearing how others here approach this and how they balance certification study with real-world practice. Did earning certifications help more in practical situations or mainly from a career and credibility point of view? And for someone early in their learning journey, what should be prioritized first?
