Model Development at Scale
In this course, you will develop an in-depth understanding of how to design, implement, and govern scalable machine learning systems that operate effectively at enterprise scale. The curriculum is organized into three experiential modules: developing distributed ML workflows with frameworks such as Apache SparkML and Ray, transitioning local ML development to distributed compute using tools like Pandas on Spark, and operationalizing and governing production models with Databricks’ MLOps ecosystem.
Through hands-on projects, you will construct end-to-end distributed ML pipelines using the SparkML workflow, applying Transformers, Estimators, and the fit/transform paradigm for both classification and regression tasks. You will version, compare, and manage experiments using MLflow 3.0 to ensure reproducibility and governance, capturing lineage between data, features, and model artifacts. Additionally, you will apply scalable Hyperparameter Optimization frameworks to improve model performance at scale.
The course concludes by demonstrating complete lifecycle management, from experimentation to production deployment, using Unity Catalog and Model Serving. You will learn to operationalize trained models, monitor their performance, and implement strong governance over models, features, and Delta assets within the Databricks environment.
⇾ Intermediate-level knowledge of traditional machine learning concepts.
⇾ Intermediate-level experience with traditional machine learning development on Databricks.
⇾ Intermediate-level knowledge of Python for machine learning projects.
⇾ Recommended: Intermediate-level experience with basic Spark concepts.
Self-Paced
Custom-fit learning paths for data, analytics, and AI roles and career paths through on-demand videos
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Self-Paced
Custom-fit learning paths for data, analytics, and AI roles and career paths through on-demand videos
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Public and private courses taught by expert instructors across half-day to two-day courses
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Self-paced and weekly instructor-led sessions for every style of learner to optimize course completion and knowledge retention. Go to Subscriptions Catalog tab to purchase
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Comprehensive training offering for large scale customers that includes learning elements for every style of learning. Inquire with your account executive for details

