Top Tweets for #MSLEARN
This module has you implement an agent executor and host a real A2A server, then connect to it — the full discovery-to-execution loop, not just the spec.
#MicrosoftFoundry #AzureAI #MSLearn #A2A (2/2)
Then persist the enriched output in a knowledge store for reuse elsewhere. That last step is what turns one-off search into a reusable data asset.
#MicrosoftFoundry #AzureAI #MSLearn #AzureAISearch (2/2)
Or training a custom model when your forms are industry-specific and nothing prebuilt fits. This module has you test both inside Document Intelligence Studio before writing extraction code.
#MicrosoftFoundry #AzureAI #MSLearn #DocumentIntelligence (2/2)
Then you run analysis entirely through calls in a client application. Use this one once you're moving past prototyping and into an actual app architecture.
#MicrosoftFoundry #AzureAI #MSLearn #MultimodalAI (2/2)
You're creating your own analyzer, configured for your specific multimodal extraction needs, then consuming it via the API — the difference between a generic tool and one tuned to your document/image/audio mix.
#MicrosoftFoundry #AzureAI #MSLearn #MultimodalAI (2/2)
The payoff here is using the Azure OpenAI SDK in Python to analyze images programmatically, not just describe them in a UI — the bridge between vision chat and structured image analysis.
#MicrosoftFoundry #AzureAI #MSLearn #ComputerVision (2/2)
It gets into remixing existing video output using the Azure OpenAI SDK in Python — the detail that gets missed when people describe this as just another text-to-video demo.
#MicrosoftFoundry #AzureAI #MSLearn #Sora2 (2/2)
That client app is built on the image-generation REST API. This module walks both paths, so you're not stuck testing in the portal forever.
#MicrosoftFoundry #AzureAI #MSLearn #GenerativeAI (2/2)
Then you build a chat app that submits image prompts programmatically. The gap between playground testing and real client code is exactly what this module closes.
#MicrosoftFoundry #AzureAI #MSLearn #ComputerVision (2/2)
This module has you wire up both, rather than assuming one API covers everything — worth knowing before you architect a multilingual app around the wrong assumption.
#MicrosoftFoundry #AzureAI #MSLearn #NLP (2/2)
This module shows both the API and SDK paths for building it, then how to plug an existing Foundry agent directly into the Voice Live pipeline — the step that turns a scripted demo into a real voice agent.
#MicrosoftFoundry #AzureAI #MSLearn #VoiceAI (2/2)
You have to set up Azure Blob Storage for audio file input and output before the agent can do anything. The module covers that setup, plus the same dynamic tool-discovery pattern MCP agents use for text.
#MicrosoftFoundry #AzureAI #MSLearn #MCP (2/2)
SSML lets you control pacing, pronunciation, and voice in the output, instead of settling for flat text-to-speech. The module also covers audio format config, which matters more than most expect in production.
#MicrosoftFoundry #AzureAI #MSLearn #AzureSpeech (2/2)
This module treats them as separate skills to build, not one generic "audio" feature. You start by choosing the right speech-capable model in Foundry before writing either path.
#MicrosoftFoundry #AzureAI #MSLearn #GenerativeAI
🔥 Orin Thomas just published a complete list of #ActiveDirectory content on #MSLearn! These are 24 modules total, from basic to advanced: Active Directory Domain Services modules on Microsoft Learn
🔗 https://t.co/they8nWv3r
#AzOps #WindowsServer #ITPro
Microsoft Learn has a CLI currently in preview. It works with Github Copilot CLI too :)
check it out below
https://t.co/z87HdZ2QEM
@MicrosoftLearn #MSLearn #MicrosoftLearn #Cloud #Microsoft @github
Got some time this evening to renew Azure Administrator Certification for another year
#AZ104 #MicrosoftLearn #MSLearn #Microosft #Cloud
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