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)"

  • Status: Preview

    Skills you'll gain: Tensorflow, Keras (Neural Network Library), Google Cloud Platform, Deep Learning, MLOps (Machine Learning Operations), Artificial Neural Networks, Data Pipelines, Data Processing, Application Deployment, Application Programming Interface (API)

  • Status: New

    Skills you'll gain: Jupyter, Google Cloud Platform, MLOps (Machine Learning Operations), Computing Platforms, Machine Learning, Development Environment, Exploratory Data Analysis

  • Status: Preview

    Skills you'll gain: Tensorflow, Keras (Neural Network Library), Google Cloud Platform, Data Pipelines, MLOps (Machine Learning Operations), Application Deployment, Deep Learning, Data Processing, Artificial Neural Networks, Data Cleansing, Data Transformation, Machine Learning, Application Programming Interface (API)

  • Status: Free Trial

    Skills you'll gain: Google Cloud Platform, Artificial Intelligence and Machine Learning (AI/ML), Responsible AI, Artificial Intelligence, Data Quality, Cloud API, Applied Machine Learning, Machine Learning, MLOps (Machine Learning Operations), Natural Language Processing, Image Analysis, Predictive Analytics

  • Status: Preview

    Skills you'll gain: Google Cloud Platform, Apache Airflow, CI/CD, Tensorflow, MLOps (Machine Learning Operations), Data Pipelines, Kubernetes, Metadata Management, PyTorch (Machine Learning Library), Continuous Deployment, Continuous Integration

  • Skills you'll gain: Large Language Modeling, Image Analysis, Cloud Services, Applied Machine Learning, Computer Vision, MLOps (Machine Learning Operations), Artificial Intelligence, Generative AI, Natural Language Processing, Document Management, Integrated Development Environments, Data Integration, Application Deployment

  • Skills you'll gain: Large Language Modeling, LLM Application, Generative AI, Prompt Engineering, Data Processing, Application Development, MLOps (Machine Learning Operations), Open Source Technology

  • Skills you'll gain: Data Ethics, Responsible AI, Data Modeling, Data Analysis, MLOps (Machine Learning Operations), Artificial Intelligence, Applied Machine Learning, Machine Learning

  • Status: Free Trial

    Skills you'll gain: AI Personalization, Data Integration, Google Cloud Platform, MLOps (Machine Learning Operations), Data Modeling, Continuous Monitoring, Data Quality, System Monitoring, Real Time Data, Enterprise Architecture, Application Programming Interface (API)

  • Skills you'll gain: Application Deployment, Image Analysis, Google Cloud Platform, Computer Vision, Anomaly Detection, MLOps (Machine Learning Operations), Predictive Modeling

  • Status: Preview

    Skills you'll gain: MLOps (Machine Learning Operations), CI/CD, Google Cloud Platform, Data Pipelines, Kubernetes, Tensorflow, Metadata Management, PyTorch (Machine Learning Library), Containerization

  • Skills you'll gain: Google Cloud Platform, Tensorflow, Kubernetes, Scalability, Application Deployment, Image Analysis, Cloud Computing, MLOps (Machine Learning Operations), System Monitoring, Cloud Management, Cloud Storage, Data Management

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