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
1online degree
166courses

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Results for "mlops (machine learning operations)"

  • 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: Free Trial

    Skills you'll gain: Data Management, Artificial Intelligence and Machine Learning (AI/ML), Infrastructure Architecture, MLOps (Machine Learning Operations), Application Deployment, Data Processing, Data Cleansing, Artificial Intelligence, Data Security, Application Frameworks, PyTorch (Machine Learning Library), Machine Learning, Tensorflow, Applied Machine Learning, Data Pipelines, Scalability

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

  • 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

  • Status: Free Trial

    Skills you'll gain: Feature Engineering, Tensorflow, Google Cloud Platform, Data Quality, Data Cleansing, Scikit Learn (Machine Learning Library), Keras (Neural Network Library), Machine Learning, Exploratory Data Analysis, Supervised Learning, MLOps (Machine Learning Operations), Jupyter, Big Data, Deep Learning, Artificial Neural Networks, Responsible AI, No-Code Development, Data Transformation, Applied Machine Learning, Data Pipelines

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

  • 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

  • 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

  • Status: Free Trial

    Skills you'll gain: MLOps (Machine Learning Operations), Continuous Delivery, Applied Machine Learning, Google Cloud Platform, Cloud Applications, Artificial Intelligence and Machine Learning (AI/ML), Cloud API, Microsoft Azure, Computer Vision, Application Programming Interface (API), Natural Language Processing, Flask (Web Framework), Automation

  • Status: Free

    Skills you'll gain: Applied Machine Learning, Machine Learning, MLOps (Machine Learning Operations), Technology Roadmaps, Data-Driven Decision-Making, Artificial Intelligence and Machine Learning (AI/ML), Business Analytics, Business Solutions, Organizational Strategy, AI Product Strategy, Organizational Change, Feasibility Studies, System Requirements, Solution Design

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

  • 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

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