MS MLO case studies
MS MLO · Put your knowledge to work in context.
The Microsoft MLO credential is a vendor-aligned certification aimed at engineers and data scientists who own the operational side of machine learning: not just training a model, but designing the solution, moving data and features through it, shipping it to an endpoint, watching it in production, and governing it responsibly. It suits practitioners who already build models in Azure Machine Learning or a comparable stack and now want to demonstrate they can run the full lifecycle repeatably. The MS MLO case studies are 5 cases and about 2,623 words.
1Batch demand forecasting for a grocery chain
A grocery chain with 620 stores and 14 distribution centers wants daily SKU-level demand forecasts for 85,000 active SKUs. Sales history is 4 years in Azure Data Lake Storage Gen2 as Parquet; store inventory snapshots arrive nightly from an on-premises SQL Server via a self-hosted integration runtime.
644 words, about 3 min2Churn model with training-serving skew
A subscription streaming service has 12 million customers. A churn model is trained on a nightly account snapshot plus 90 days of clickstream events archived from Event Hubs to Parquet.
520 words, about 3 min3Rare-defect image classifier tuning
A semiconductor manufacturer trains an image classifier to detect 18 defect classes on production-line images. The dataset has 240,000 labeled images; the rarest class has 380 examples, the most common 61,000.
474 words, about 2 min4Low-latency fraud model releases on AKS
A payments company runs a fraud model on Azure Kubernetes Service. Peak traffic is 9,000 transactions/sec, the p99 latency budget is 45 ms, and the model must be refreshed daily.
513 words, about 3 min5Regulated credit-model release pipeline
A bank’s credit underwriting team maintains a gradient-boosted model used for 400,000 applications per month. Regulators require every production model to be traceable to a code commit, training-data snapshot, and approval; no direct production changes; fairness review for age and postal-code proxies; and PII must not leave a governed subscription.
472 words, about 2 min