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

    4.2 stars, 650 reviews, Advanced, Specialization, 3 - 6 Months

  • 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, 514 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

  • 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, 494 reviews, Intermediate, Course, 1 - 4 Weeks

  • Duke University

    Skills you'll gain: MLOps (Machine Learning Operations), GitHub Copilot, Responsible AI, Model Deployment, Containerization, Web Frameworks, Rust (Programming Language), AI Workflows, DevOps, Hugging Face, Applied Machine Learning, Cloud Solutions, Cloud-Native Computing, Machine Learning, Serverless Computing, Application Deployment, GitHub, Command-Line Interface, Big Data

    4.1 stars, 236 reviews, Advanced, Course, 1 - 3 Months

  • Microsoft

    Skills you'll gain: MLOps (Machine Learning Operations), Feature Engineering, Microsoft Azure, Model Deployment, CI/CD, Continuous Deployment, Fine-tuning, Model Training, Kubernetes, Model Optimization, Apache Kafka, Real Time Data, Application Deployment, Transfer Learning, AWS Kinesis, Data Architecture, Cloud Computing, Machine Learning, Data Science, Information Technology

    Advanced · Course · 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

  • Pearson

    Skills you'll gain: MLOps (Machine Learning Operations), Model Deployment, Data Processing, Model Training, Data Collection, Data Management, Cloud Deployment, Model Evaluation, Data Preprocessing, Automation, Data Pipelines, Feature Engineering, Continuous Monitoring

    Intermediate · Course · 1 - 4 Weeks

  • Duke University

    Skills you'll gain: AWS SageMaker, MLOps (Machine Learning Operations), Microsoft Azure, Model Deployment, Data Engineering, Exploratory Data Analysis, Data Pipelines, Model Training, Amazon Web Services, Feature Engineering, Cloud Solutions, Artificial Intelligence and Machine Learning (AI/ML), Model Evaluation, Data Preprocessing, Cloud Deployment, Data Analysis, Applied Machine Learning, Machine Learning Methods, Machine Learning, Python Programming

    3.6 stars, 61 reviews, Advanced, Course, 1 - 3 Months

  • Edureka

    Skills you'll gain: MLOps (Machine Learning Operations), Feature Engineering, AWS SageMaker, DevOps, CI/CD, Kubernetes, Cloud-Native Computing, Model Training, Fraud detection, Continuous Deployment, Devops Tools, AI Workflows, Application Deployment, Continuous Integration, Site Reliability Engineering, Application Lifecycle Management, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Scalability, Artificial Intelligence

    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

  • Duke University

    Skills you'll gain: Pandas (Python Package), MLOps (Machine Learning Operations), NumPy, Unit Testing, Model Deployment, Data Manipulation, Test Script Development, Software Testing, Data Import/Export, Applied Machine Learning, Test Automation, Data Wrangling, Python Programming, Code Reusability, Data Processing, Debugging, Data Structures, Machine Learning, Object Oriented Programming (OOP), Scripting

    4.2 stars, 385 reviews, Intermediate, Course, 1 - 3 Months