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: New

    Skills you'll gain: MLOps (Machine Learning Operations), Google Cloud Platform, Tensorflow, Applied Machine Learning, Data Validation, Machine Learning, Systems Design, Systems Architecture, Distributed Computing, Performance Tuning, Data Pipelines, Scalability, Data Processing, Hybrid Cloud Computing, Debugging

  • Status: Preview

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

  • 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

  • Skills you'll gain: Data Ethics, Responsible AI, Data Modeling, Data Analysis, MLOps (Machine Learning Operations), Artificial Intelligence, Applied Machine Learning, Machine Learning

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

  • 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

  • Status: New

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

  • Skills you'll gain: Google Cloud Platform, Tensorflow, Kubernetes, Scalability, Application Deployment, Image Analysis, Cloud Computing, MLOps (Machine Learning Operations), System Monitoring, Cloud Management, Cloud Storage, Data Management

  • Skills you'll gain: Responsible AI, Data Ethics, Artificial Intelligence, Google Cloud Platform, MLOps (Machine Learning Operations), Machine Learning, Data Quality

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