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)"

  • Duke University

    Skills you'll gain: Fine-tuning, MLOps (Machine Learning Operations), Model Deployment, Cloud Deployment, Pandas (Python Package), AWS SageMaker, NumPy, Microsoft Azure, Hugging Face, GitHub Copilot, Unit Testing, Data Engineering, DevOps, Cloud Computing, Python Programming, Machine Learning, GitHub, Big Data, Data Management, Data Analysis

    4.1 stars, 642 reviews, Advanced, Specialization, 3 - 6 Months

  • Google Cloud

    Skills you'll gain: MLOps (Machine Learning Operations), Model Deployment, Google Cloud Platform, Model Evaluation, Model Training, DevOps, Cloud Deployment, Devops Tools, Continuous Deployment, CI/CD, AI Workflows, Automation

    4 stars, 489 reviews, Intermediate, Course, 1 - 4 Weeks

  • Board Infinity

    Skills you'll gain: Anomaly Detection, Feature Engineering, Fraud detection, Unsupervised Learning, Continuous Monitoring, Autoencoders, MLOps (Machine Learning Operations), Machine Learning Methods, Statistical Machine Learning, Model Training, Time Series Analysis and Forecasting, System Monitoring, Applied Machine Learning, Model Deployment, Statistical Analysis, Taxonomy

    Beginner · Course · 1 - 4 Weeks

  • Google Cloud

    Skills you'll gain: MLOps (Machine Learning Operations), Model Evaluation, Model Deployment, AI Orchestration, AI Workflows, Generative AI, Google Cloud Platform, Data Modeling, Continuous Monitoring, Data Pipelines, Model Training, Feature Engineering, Model Optimization, DevOps, Agentic Workflows, Generative AI Agents, Cloud Deployment, Devops Tools, Data Store, Continuous Deployment

    4 stars, 509 reviews, Intermediate, Specialization, 3 - 6 Months

  • Board Infinity

    Skills you'll gain: Model Deployment, AWS SageMaker, MLOps (Machine Learning Operations), Serverless Computing, Google Cloud Platform, Cloud Deployment, AI Integrations, Docker (Software), Cloud Platforms, Cloud Computing, Containerization, Application Deployment, Amazon Web Services, Restful API, DevOps, CI/CD, Microsoft Azure, Public Cloud, Microservices, Devops Tools

    Beginner · Specialization · 1 - 3 Months

  • KodeKloud

    Skills you'll gain: MLOps (Machine Learning Operations), Model Deployment, Data Architecture, Model Training, Apache Airflow, Data Pipelines, Apache Kafka, DevOps, CI/CD, Apache Spark, Pandas (Python Package), Deep Learning, Data Governance, Machine Learning, Supervised Learning, Flask (Web Framework), Grafana, Python Programming, Unsupervised Learning, Automation

    Beginner · Specialization · 1 - 3 Months

  • Board Infinity

    Skills you'll gain: Feature Engineering, Model Evaluation, Model Deployment, Fine-tuning, Data Preprocessing, Model Training, Deep Learning, Machine Learning Methods, Model Optimization, Scikit Learn (Machine Learning Library), PyTorch (Machine Learning Library), Scalability, Hugging Face, Docker (Software), Supervised Learning, Machine Learning Algorithms, MLOps (Machine Learning Operations), Applied Machine Learning, Software Development, Machine Learning

    Intermediate · Specialization · 1 - 3 Months

  • Google Cloud

    Skills you'll gain: MLOps (Machine Learning Operations), Model Deployment, Data Modeling, Google Cloud Platform, Feature Engineering, Model Training, Data Store, Data Preprocessing, Data Processing, Data Management, Data Storage Technologies

    4 stars, 20 reviews, Intermediate, Course, 1 - 4 Weeks

  • Microsoft

    Skills you'll gain: Responsible AI, MLOps (Machine Learning Operations), Azure DevOps Pipelines, Azure DevOps, Generative AI, Microsoft Azure, Model Deployment, AI Workflows, Model Training, CI/CD, Version Control, Data Ethics, Model Evaluation, Continuous Integration, Git (Version Control System), Continuous Monitoring

    Intermediate · Course · 1 - 4 Weeks

  • Whizlabs

    Skills you'll gain: MLOps (Machine Learning Operations), Data Preprocessing, AWS SageMaker, Model Evaluation, Model Deployment, Artificial Intelligence and Machine Learning (AI/ML), Amazon Web Services, Model Training, Predictive Modeling, Machine Learning Methods, Applied Machine Learning, Data Processing, Machine Learning, Supervised Learning, Machine Learning Algorithms, Unsupervised Learning, Classification Algorithms

    4.3 stars, 7 reviews, Intermediate, Course, 1 - 4 Weeks

  • Coursera

    Skills you'll gain: MLOps (Machine Learning Operations), Model Deployment, CI/CD, Continuous Deployment, Docker (Software), Kubernetes, Model Training, Containerization, AI Workflows, Model Optimization, Scalability, Devops Tools, DevOps, Continuous Monitoring

    Intermediate · Course · 1 - 4 Weeks

  • KodeKloud

    Skills you'll gain: AWS SageMaker, Model Deployment, MLOps (Machine Learning Operations), Data Governance, Model Training, Data Security, Amazon Web Services, Application Deployment, General Data Protection Regulation (GDPR), Model Optimization, Information Privacy

    Beginner · Course · 1 - 4 Weeks