MLOps (Machine Learning Operations)

MLOps (Machine Learning Operations) is an engineering discipline that aims to unify machine learning system development and machine learning system operations. Coursera's MLOps catalogue teaches you how to streamline and regulate the process of deploying, testing, and improving machine learning models in production. You'll learn about essential elements of MLOps such as data and model versioning, model testing, monitoring, and validation, as well as robust strategies for deploying and maintaining ML models. By the end of your learning journey, you will be able to effectively manage the ML lifecycle, understand the role of automation in MLOps, and leverage best practices to bring data science and IT operations together.
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Results for "mlops (machine learning operations)"

  • Google Cloud

    Skills you'll gain: Responsible AI, Data Ethics, Google Cloud Platform, Artificial Intelligence, Open Source Technology, Machine Learning Methods, MLOps (Machine Learning Operations), Data Quality

    Intermediate · Course · 1 - 3 Months

  • Status: New

    Google Cloud

    Skills you'll gain: Google Gemini, Generative AI, Responsible AI, Google Cloud Platform, AI Product Strategy, Data Governance, Cloud Infrastructure, Cloud Computing Architecture, Decision Making, MLOps (Machine Learning Operations), Business

    Beginner · Course · 1 - 3 Months

  • Status: New

    Google Cloud

    Skills you'll gain: Jupyter, MLOps (Machine Learning Operations), Google Cloud Platform, Artificial Intelligence and Machine Learning (AI/ML), Data Analysis

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial

    Google Cloud

    Skills you'll gain: Responsible AI, Data Ethics, Artificial Intelligence and Machine Learning (AI/ML), Artificial Intelligence, MLOps (Machine Learning Operations)

    Intermediate · Course · 1 - 4 Weeks

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