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.
40credentials
2online degrees
170courses

Results for "mlops (machine learning operations)"

  • Status: Preview

    Skills you'll gain: Big Data, Data Analysis, Applied Machine Learning, MLOps (Machine Learning Operations), Machine Learning, Predictive Modeling

  • Status: Preview

    Skills you'll gain: MLOps (Machine Learning Operations), Google Cloud Platform, Data Infrastructure, Machine Learning, Systems Design, Data Processing, Data Pipelines, Data Architecture, Big Data, Cloud Engineering, Data Visualization, Cloud Security, Data Storage, Scalability

  • Status: New

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

  • Skills you'll gain: Feature Engineering, Tensorflow, MLOps (Machine Learning Operations), Data Pipelines, Data Processing, Keras (Neural Network Library), Data Transformation, Applied Machine Learning, Machine Learning, Statistical Methods

  • Status: Preview

    Skills you'll gain: CI/CD, Apache Airflow, Data Pipelines, MLOps (Machine Learning Operations), Google Cloud Platform, Tensorflow, Kubernetes, Metadata Management, Machine Learning Methods, Containerization, Data Processing, Data Validation

  • Status: New
    Status: Free Trial

    Skills you'll gain: AWS SageMaker, AWS Kinesis, Amazon Redshift, Cloud Security, MLOps (Machine Learning Operations), Amazon S3, Amazon CloudWatch, AWS Identity and Access Management (IAM), Data Pipelines, Real Time Data, Feature Engineering, Data Storage, Data Security, Encryption

  • Status: Preview

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

  • 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)

  • Status: Preview

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

  • Skills you'll gain: Tensorflow, Keras (Neural Network Library), Google Cloud Platform, MLOps (Machine Learning Operations), Deep Learning, Data Transformation, Data Processing, Data Pipelines, Artificial Neural Networks, Machine Learning, Scalability, 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

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

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