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.

Filter by

Skip to search results

Subject
Required

Language
Required

The language used throughout the course, in both instruction and assessments.

Learning Product
Required

Build job-relevant skills in under 2 hours with hands-on tutorials.
Learn from top instructors with graded assignments, videos, and discussion forums.
Get in-depth knowledge of a subject by completing a series of courses and projects.

Level
Required

Duration
Required

Subtitles
Required

Educator
Required

Hands-on Learning
Required

Tools
Required

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, 649 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, 493 reviews, Intermediate, Course, 1 - 4 Weeks

  • 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

  • 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

  • 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

  • Microsoft

    From the course: Advanced AI and Machine Learning Techniques and Capstone·Lesson: Optimizing ML pipelines

    Watch now

    ·

    3.2k views

    Micro Lesson · 4 minutes

  • Microsoft

    From the course: MLOps and responsible AI practices·Lesson: Fundamentals of MLOps

    Watch now

    ·

    668 views

    Micro Lesson · 3 minutes

  • Packt

    From the course: Advanced Deployment, MLOps, and Generative AI in Azure·Lesson: MLOps (Machine Learning Operations)

    Watch now

    ·

    69 views

    Micro Lesson · 10 minutes

  • 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, Continuous Integration, Application Deployment, Site Reliability Engineering, Application Lifecycle Management, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Scalability, Artificial Intelligence

    Intermediate · Specialization · 1 - 3 Months