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: Data Ethics, Responsible AI, Applied Machine Learning, MLOps (Machine Learning Operations), Machine Learning, Software Visualization, Data Integrity, Artificial Intelligence

  • Status: New

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

  • Status: New
    Status: Free Trial

    Skills you'll gain: AWS Identity and Access Management (IAM), Identity and Access Management, Amazon Web Services, Data Ethics, Generative AI, AWS SageMaker, Cloud Security, MLOps (Machine Learning Operations), Data Security, Role-Based Access Control (RBAC), Data Governance, Artificial Intelligence, Encryption, Public Cloud, General Data Protection Regulation (GDPR)

  • Status: Preview

    Skills you'll gain: Google Gemini, Generative AI, Prompt Engineering, AI Product Strategy, Multimodal Prompts, MLOps (Machine Learning Operations), LLM Application, Google Cloud Platform

  • Status: Preview

    Skills you'll gain: Google Gemini, Generative AI, Multimodal Prompts, Prompt Engineering, AI Product Strategy, Google Cloud Platform, Prototyping, MLOps (Machine Learning Operations), Product Lifecycle Management, Application Lifecycle Management, Project Design

  • Skills you'll gain: Big Data, Analytics, Data Analysis, Applied Machine Learning, MLOps (Machine Learning Operations), Google Cloud Platform, Machine Learning, Predictive Modeling, SQL

  • Status: New

    Skills you'll gain: Jupyter, MLOps (Machine Learning Operations), Google Cloud Platform, Virtual Machines, Machine Learning, Development Environment, Collaborative Software

  • Skills you'll gain: Cloud Computing, Istio, Tensorflow, Google Cloud Platform, MLOps (Machine Learning Operations), Kubernetes, Application Deployment, Continuous Deployment, Microservices, Load Balancing

  • Status: Preview

    Skills you'll gain: Prompt Engineering, Google Gemini, Multimodal Prompts, Generative AI, Generative Model Architectures, Application Lifecycle Management, AI Product Strategy, Prototyping, MLOps (Machine Learning Operations), LLM Application, Google Cloud Platform

  • Skills you'll gain: Predictive Analytics, Big Data, Predictive Modeling, Advanced Analytics, Analytics, Applied Machine Learning, Google Cloud Platform, MLOps (Machine Learning Operations), Data Analysis, Machine Learning Methods, Data Modeling

  • Skills you'll gain: Google Cloud Platform, Data Lakes, Metadata Management, Taxonomy, MLOps (Machine Learning Operations)

  • Status: New

    Skills you'll gain: Google Gemini, Generative AI, AI Product Strategy, Google Cloud Platform, Responsible AI, Business Solutions, Cloud Computing, Innovation, MLOps (Machine Learning Operations)

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