AI-300 Labs

Lab exercises for AI-300: Operationalizing Machine Learning and Generative AI Solutions. Includes Microsoft Learn and Microsoft GitHub labs.

Experiment with Azure Machine LearningExplore Azure Machine Learning workspace resources and assetsWork with compute targets in Azure Machine LearningRun a training script as a command jobPerform hyperparameter tuning with Azure Machine LearningTune hyperparameters in Azure DatabricksUse MLflow in Azure DatabricksUse AutoML in Azure DatabricksTrain a machine learning model in Azure DatabricksManage a machine learning model in productionTrain deep learning models on Azure DatabricksRun pipelines in Azure Machine LearningCreate and explore the Responsible AI dashboard for a model in Azure Machine LearningTrigger Azure Machine Learning jobs with GitHub ActionsTrigger GitHub Actions with feature-based developmentWork with environments in GitHub ActionsDeploy a model with GitHub ActionsPlan and prepare a GenAIOps solutionManage prompts for agents in Microsoft Foundry with GitHubEvaluate and optimize AI agents through structured experimentsAutomate AI evaluations with Microsoft Foundry and GitHub ActionsEvaluate risk and safety metrics for a generative AI appGenerate a synthetic dataset for generative AI evaluationEvaluate generative AI model performanceExplore foundation models in the model catalogExplore language models in Azure DatabricksSet up RAG with Azure DatabricksImplement multi-stage reasoning with LangChainFine-tune a language model with Azure DatabricksOptimize and fine-tune AI agents for productionEvaluate a language model with Azure DatabricksImplement LLMOps in Azure DatabricksMonitor your generative AI applicationAnalyze and debug your generative AI app with tracingText guardrailsImage guardrailsGroundedness detectionPrompt ShieldsSecure Azure OpenAI with content safety controls