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.
38credentials
2online degrees
170courses

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Results for "mlops (machine learning operations)"

  • Status: Preview

    Skills you'll gain: MLOps (Machine Learning Operations), Google Cloud Platform, Cloud Management, DevOps, Continuous Deployment, Automation, Application Deployment, Applied Machine Learning, Machine Learning, Software Development Life Cycle, Continuous Integration, Data Processing

  • Status: New

    Skills you'll gain: MLOps (Machine Learning Operations), AWS SageMaker, CI/CD, DevOps, Data Processing, Data Management, Machine Learning, Predictive Modeling, Automation, Data Pipelines, Applied Machine Learning, Continuous Monitoring

  • Skills you'll gain: MLOps (Machine Learning Operations), Generative AI, Responsible AI, Security Testing, Predictive Modeling, Verification And Validation, Data Validation, Machine Learning

  • Status: Preview

    Skills you'll gain: MLOps (Machine Learning Operations), Google Cloud Platform, DevOps, Applied Machine Learning, Continuous Deployment, Automation, Continuous Integration, Continuous Monitoring, Scalability, Data Management

  • Status: Preview

    Skills you'll gain: Generative AI, Large Language Modeling, MLOps (Machine Learning Operations), Artificial Intelligence, Cloud Computing, Cloud Infrastructure, Infrastructure Architecture, Data Infrastructure, Artificial Neural Networks, IT Infrastructure, Information Technology Operations, Deep Learning, Network Infrastructure, Tensorflow, Hardware Architecture, Machine Learning, PyTorch (Machine Learning Library), Data Centers, Computer Architecture

  • Status: Free Trial

    Skills you'll gain: Prompt Engineering, Google Cloud Platform, Generative AI, Cloud Infrastructure, MLOps (Machine Learning Operations), Cloud Platforms, Artificial Intelligence, Machine Learning, Natural Language Processing

  • Status: Free Trial

    Skills you'll gain: Microsoft Azure, MLOps (Machine Learning Operations), Databricks, Cloud Computing, Data Ethics, Data Pipelines, Responsible AI, Machine Learning, Information Privacy, Continuous Monitoring, Data Security, Performance Tuning, Scalability

  • Status: Preview

    Skills you'll gain: MLOps (Machine Learning Operations), Generative AI, Predictive Modeling, Responsible AI, Google Cloud Platform, Machine Learning, Data Quality

  • Status: New
    Status: Free Trial

    Skills you'll gain: Responsible AI, MLOps (Machine Learning Operations), Artificial Intelligence and Machine Learning (AI/ML), Jenkins, Applied Machine Learning, CI/CD, Java, Continuous Deployment, Java Programming, Artificial Intelligence, Machine Learning, Spring Framework, Application Deployment, Reinforcement Learning, Spring Boot, Enterprise Application Management, Continuous Monitoring, Enterprise Architecture

  • Skills you'll gain: MLOps (Machine Learning Operations), Generative AI, Continuous Monitoring, Google Cloud Platform, Predictive Modeling, Applied Machine Learning, Verification And Validation, Performance Testing, Machine Learning

  • Skills you'll gain: Generative AI, MLOps (Machine Learning Operations), Continuous Monitoring, Statistical Methods, Responsible AI, Predictive Modeling, Google Cloud Platform, Machine Learning, Natural Language Processing

  • Skills you'll gain: Generative AI, Google Cloud Platform, MLOps (Machine Learning Operations), Predictive Modeling, Continuous Monitoring, Machine Learning Methods, Responsible AI, Applied Machine Learning