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)"

  • Skills you'll gain: MLOps (Machine Learning Operations), Google Cloud Platform, Feature Engineering, Data Processing, Data Modeling, Data Management, Application Deployment, Continuous Deployment, Data Storage

  • Status: New

    Skills you'll gain: Generative AI, MLOps (Machine Learning Operations), Google Cloud Platform, Continuous Monitoring, Responsible AI, Machine Learning, A/B Testing

  • Skills you'll gain: Data Management, Data Governance, MLOps (Machine Learning Operations), Forecasting, Google Cloud Platform, Data Pipelines, Predictive Analytics, Predictive Modeling, Applied Machine Learning, Data Processing, Machine Learning, Feature Engineering, Data Transformation, Performance Tuning

  • Skills you'll gain: MLOps (Machine Learning Operations), Google Cloud Platform, Feature Engineering, Data Modeling, Data Storage, Continuous Deployment, Data Processing, Data Management, Data Quality

  • Status: Free Trial

    Skills you'll gain: MLOps (Machine Learning Operations), Data Management, Data Quality, Technical Management, Applied Machine Learning, Project Management, Data Processing, Artificial Intelligence and Machine Learning (AI/ML), Software Development Life Cycle, Machine Learning, Data Cleansing, Data Pipelines, Technical Design, Technology Solutions, Systems Design, Data Collection, Data Science, Systems Architecture, Feature Engineering, System Monitoring

  • Skills you'll gain: Generative AI, Google Cloud Platform, MLOps (Machine Learning Operations), Cloud Infrastructure, Artificial Intelligence and Machine Learning (AI/ML), Tensorflow, Applied Machine Learning, Large Language Modeling, Artificial Intelligence, Data Processing, Machine Learning, Predictive Modeling, Natural Language Processing

  • Status: Free Trial

    Skills you'll gain: Google Cloud Platform, MLOps (Machine Learning Operations), Applied Machine Learning, Machine Learning, Unstructured Data, Advanced Analytics, Predictive Modeling, Jupyter, Data Pipelines, Artificial Intelligence, Natural Language Processing

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

  • Skills you'll gain: Google Cloud Platform, Unstructured Data, MLOps (Machine Learning Operations), Big Data, Data Pipelines, Applied Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Cloud API, Jupyter, Machine Learning, Natural Language Processing

  • Status: Preview

    Skills you'll gain: MLOps (Machine Learning Operations), Data Management, Google Cloud Platform, Data Governance, Workflow Management, Applied Machine Learning, Data Pipelines, Machine Learning, Predictive Modeling, Feature Engineering, Continuous Monitoring

  • Skills you'll gain: Google Cloud Platform, Unstructured Data, Tensorflow, MLOps (Machine Learning Operations), Data Pipelines, Applied Machine Learning, Big Data, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Jupyter

  • Status: Preview

    Skills you'll gain: MLOps (Machine Learning Operations), CI/CD, Continuous Deployment, Docker (Software), Kubernetes, Containerization, Scalability, Continuous Integration, DevOps, Data Infrastructure, IT Infrastructure, Infrastructure Architecture, Cloud Infrastructure, Artificial Intelligence and Machine Learning (AI/ML), Continuous Monitoring, Real Time Data, Version Control

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