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- AI
- Data
Machine Learning Engineering
11 Courses
5 Labs
14 Hours
Skill IQ
On completion of this path, the learner will be able to design and operationalize solutions to maximize the performance and scale of Machine Learning. These solutions will include Machine Learning infrastructure, data and feature quality processes, model formats and training (Real and Batch), in addition to model deployment options - real-time model serving and batch model scoring, monitoring model performance & reliability, scaling Machine Learning models and automated Machine Learning interventions.
Content in this path
Machine Learning Engineering
Watch the courses in this section to understand Machine Learning Engineering!
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What You'll Learn
- How to demystify Machine Learning Operations (MLOps)
- How to productionalize Data Pipelines with Apache Airflow 1
- How to implement principles for Data Quality Measures
Prerequisites
- Machine Learning Literacy
Related topics
- Data Pipelines
- Data Engineering
- Machine Learning
- MLOps
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