As an intermediate-level data scientist or machine learning engineer, you know that you can use Azure Databricks to accelerate AI and innovation, with a single, cloud-based platform for big data processing, analytics, and machine learning. You can use also use it for complex forecasting, computer vision, natural language processing, and other AI workloads. If you’d like to build on your knowledge, I encourage you to check out the Machine learning with Azure Databricks learning path on Microsoft Learn. In these modules, find out how Azure Databricks makes it simple to run large-scale Spark workloads to transform, analyze, and visualize data. Train a predictive model, manage the machine learning lifecycle with MLflow, and build an effective machine learning model for your data with AutoML. With this practical learning path, get big details on big data, as you #LearnMicrosoftAI.
