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.
42credentials
2online degrees
170courses

Results for "mlops (machine learning operations)"

  • Status: Free Trial

    Skills you'll gain: MLOps (Machine Learning Operations), Application Deployment, Containerization, CI/CD, Docker (Software), Microsoft Azure, Cloud Computing, Cloud Applications, Machine Learning Software, GitHub, Application Programming Interface (API)

  • 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: New

    Skills you'll gain: Responsible AI, Exploratory Data Analysis, Data Storytelling, Data Presentation, Dashboard, Data Literacy, No-Code Development, Business Analytics, Data Science, Applied Machine Learning, Data Capture, Data Modeling, Data Processing, Data Transformation, Data Ethics, MLOps (Machine Learning Operations), Machine Learning, Data Analysis, Predictive Modeling, Data Visualization

  • 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

  • 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 Trial

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

  • Status: Free Trial

    Skills you'll gain: MLOps (Machine Learning Operations), Google Cloud Platform, Data Management, Data Governance, Workflow Management, Tensorflow, Applied Machine Learning, Data Pipelines, Machine Learning, Cloud Computing, Data Transformation, Continuous Monitoring

  • Status: Free Trial

    Skills you'll gain: Feature Engineering, Responsible AI, Generative AI, Tensorflow, Generative AI Agents, Keras (Neural Network Library), Data Quality, MLOps (Machine Learning Operations), Exploratory Data Analysis, Machine Learning Methods, Machine Learning, Applied Machine Learning, Google Cloud Platform, Artificial Intelligence and Machine Learning (AI/ML), Scikit Learn (Machine Learning Library), Data Cleansing, Prompt Engineering, Data Strategy, OpenAI, Cloud Computing

  • Status: Free

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

  • Status: New
    Status: Free Trial

    Skills you'll gain: Generative AI, Supervised Learning, Generative Model Architectures, Unsupervised Learning, Large Language Modeling, Time Series Analysis and Forecasting, Exploratory Data Analysis, LLM Application, Applied Machine Learning, Data Collection, Machine Learning Algorithms, OpenAI, Feature Engineering, Data Ethics, Dimensionality Reduction, MLOps (Machine Learning Operations), Machine Learning, Multimodal Prompts, Data Processing, Network Architecture

  • Status: Free Trial

    Skills you'll gain: AWS Kinesis, AWS SageMaker, Machine Learning Algorithms, Data Collection, Amazon Redshift, MLOps (Machine Learning Operations), Image Analysis, Reinforcement Learning, Amazon Web Services, Scalability, Forecasting, Feature Engineering, Algorithms, Machine Learning, Technical Design, Data Analysis, Real Time Data, Predictive Modeling, Applied Machine Learning, Data Modeling

  • Status: Preview

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

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