Data Science

MLOps1 (Azure): Deploying AI & ML Models in Production using Microsoft Azure ML

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The material equips data engineers to incorporate machine learning models into pipelines while adhering to best practices in collaboration, version control, and artifact management.

Key AI Functions:machine learning, data engineering, ai, roi, microsoft azure, data science, software versioning, ops, forecasting, ai & machine learning

Description for MLOps1 (Azure): Deploying AI & ML Models in Production using Microsoft Azure ML

  • Collaborating with Data Scientists: Comprehend the essential abilities required for data engineers to collaborate effectively with data scientists.

  • Integration of Machine Learning: Acquire the skills to utilize machine learning models for predictive analytics and incorporate them into automated workflows.

  • Performance Evaluation: Assess the efficacy of models and pipelines while documenting pertinent indicators.

  • Versioning and Artifact Management: Implement optimal techniques for versioning models and data, and oversee the management of model and data artifacts.

Level: Intermediate

Certification Degree: Yes

Languages the Course is Available: 1

Offered by: On edX provided by Statistics.comX

Duration: 5�7 hours per week 4 weeks (approximately)

Schedule: Flexible

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