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: Free Trial

    Skills you'll gain: MLOps (Machine Learning Operations), Pandas (Python Package), AWS SageMaker, NumPy, Microsoft Azure, Application Deployment, Responsible AI, Data Manipulation, Exploratory Data Analysis, Containerization, Data Pipelines, CI/CD, DevOps, Cloud Computing, Python Programming, Machine Learning, GitHub, Big Data, Data Management, Data Analysis

  • Status: Free Trial

    Skills you'll gain: MLOps (Machine Learning Operations), Google Cloud Platform, Cloud Management, DevOps, Continuous Deployment, CI/CD, Machine Learning, Automation, Data Pipelines, Version Control

  • Skills you'll gain: MLOps (Machine Learning Operations), Application Deployment, Continuous Deployment, Software Development Life Cycle, Machine Learning, Applied Machine Learning, Data Validation, Feature Engineering, Data Quality, Data-Driven Decision-Making, Continuous Monitoring, Data Pipelines

  • Status: New
    Status: Free Trial

    Skills you'll gain: MLOps (Machine Learning Operations), AWS SageMaker, Artificial Intelligence and Machine Learning (AI/ML), Amazon Web Services, Predictive Modeling, Applied Machine Learning, Data Processing, Regression Analysis, Machine Learning, Supervised Learning, Feature Engineering, Data Cleansing, Continuous Deployment, Unsupervised Learning

  • Status: New

    Skills you'll gain: MLOps (Machine Learning Operations), AWS SageMaker, CI/CD, DevOps, Data Processing, Data Management, Machine Learning, Predictive Modeling, Automation, Data Pipelines, Applied Machine Learning, Continuous Monitoring

  • Status: Free Trial

    Skills you'll gain: Natural Language Processing, MLOps (Machine Learning Operations), Tensorflow, Large Language Modeling, Reinforcement Learning, Computer Vision, Google Cloud Platform, Keras (Neural Network Library), Systems Design, Image Analysis, AI Personalization, Hybrid Cloud Computing, Applied Machine Learning, Systems Architecture, Performance Tuning, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Artificial Neural Networks, Machine Learning, Machine Learning Algorithms

What brings you to Coursera today?

  • Status: New
    Status: Free Trial

    Skills you'll gain: Responsible AI, MLOps (Machine Learning Operations), Artificial Intelligence and Machine Learning (AI/ML), Jenkins, CI/CD, Java, Continuous Deployment, Java Programming, Artificial Intelligence, Apache Spark, Applied Machine Learning, Decision Tree Learning, Deep Learning, Machine Learning, Fraud detection, Spring Boot, Natural Language Processing, Regression Analysis, Reinforcement Learning, Debugging

  • Status: Free Trial

    Alberta Machine Intelligence Institute

    Skills you'll gain: Supervised Learning, Feature Engineering, Responsible AI, Machine Learning Algorithms, Data Ethics, Applied Machine Learning, Data Quality, Data Processing, MLOps (Machine Learning Operations), Jupyter, Data Validation, Machine Learning, Business Operations, Data Cleansing, Product Lifecycle Management, Machine Learning Methods, Ethical Standards And Conduct, Classification And Regression Tree (CART), Test Data, Project Management

  • Status: Free

    Skills you'll gain: MLOps (Machine Learning Operations), AWS SageMaker, Amazon Web Services, Machine Learning, Applied Machine Learning, Predictive Modeling

  • Status: Free Trial

    Skills you'll gain: Feature Engineering, MLOps (Machine Learning Operations), Prompt Engineering, Google Cloud Platform, Generative AI, Tensorflow, Keras (Neural Network Library), Apache Airflow, Cloud Infrastructure, CI/CD, Data Pipelines, Systems Design, Cloud Platforms, Data Management, Data Governance, Hybrid Cloud Computing, Workflow Management, Artificial Intelligence, Machine Learning, Cloud Computing

  • Status: Free Trial

    Skills you'll gain: Feature Engineering, Prompt Engineering, Google Cloud Platform, Generative AI, Tensorflow, Keras (Neural Network Library), MLOps (Machine Learning Operations), Cloud Infrastructure, Data Pipelines, Cloud Platforms, Data Management, Data Governance, Workflow Management, Artificial Intelligence, Deep Learning, Applied Machine Learning, Machine Learning, Cloud Computing, Data Processing, Artificial Neural Networks

  • Status: New
    Status: Free Trial

    Skills you'll gain: AWS SageMaker, MLOps (Machine Learning Operations), Feature Engineering, AI Personalization, Amazon Web Services, Artificial Intelligence and Machine Learning (AI/ML), Artificial Intelligence, Amazon Elastic Compute Cloud, Data Cleansing, Data Processing, Data Wrangling, Data Integrity, Machine Learning, Machine Learning Algorithms, Data Modeling, Supervised Learning, Data Mining, Random Forest Algorithm, Data Management, Unsupervised Learning

What brings you to Coursera today?

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