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
164courses

Most popular

Trending now

New releases

Filter by

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.
Learn a new tool or skill in an interactive, hands-on environment.
Get in-depth knowledge of a subject by completing a series of courses and projects.
Earn career credentials from industry leaders that demonstrate your expertise.

Level
Required

Duration
Required

Subtitles
Required

Educator
Required

Results for "mlops (machine learning operations)"

  • Skills you'll gain: MLOps (Machine Learning Operations), Generative AI, Responsible AI, Security Testing, Predictive Modeling, Verification And Validation, Data Validation, Machine Learning

  • 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

    Skills you'll gain: Applied Machine Learning, Machine Learning, MLOps (Machine Learning Operations), Technology Roadmaps, Data-Driven Decision-Making, Artificial Intelligence and Machine Learning (AI/ML), Business Analytics, Business Solutions, Organizational Strategy, AI Product Strategy, Organizational Change, Feasibility Studies, System Requirements, Solution Design

  • Skills you'll gain: Big Data, Data Analysis, Google Cloud Platform, Applied Machine Learning, MLOps (Machine Learning Operations), Statistical Inference, Machine Learning Methods, Machine Learning Algorithms

  • Status: Free Trial

    Skills you'll gain: Unsupervised Learning, Scikit Learn (Machine Learning Library), PyTorch (Machine Learning Library), Exploratory Data Analysis, Deep Learning, Microsoft Azure, Data Visualization, Regression Analysis, Predictive Modeling, Data Analysis, Image Analysis, Pandas (Python Package), Jupyter, Artificial Intelligence and Machine Learning (AI/ML), Classification And Regression Tree (CART), Data Science, MLOps (Machine Learning Operations), Machine Learning, Tensorflow, Artificial Neural Networks

  • Status: Free Trial

    Skills you'll gain: Feature Engineering, Responsible AI, Tensorflow, Keras (Neural Network Library), Google Cloud Platform, Data Quality, Applied Machine Learning, Data Cleansing, Machine Learning, Data Pipelines, Data Strategy, Supervised Learning, Machine Learning Algorithms, Deep Learning, Performance Tuning, Artificial Intelligence and Machine Learning (AI/ML), MLOps (Machine Learning Operations), Dataflow, Artificial Neural Networks, Data Processing

  • Status: Free Trial

    Skills you'll gain: Feature Engineering, Tensorflow, Google Cloud Platform, Data Quality, Data Cleansing, Keras (Neural Network Library), Scikit Learn (Machine Learning Library), Machine Learning, Exploratory Data Analysis, Supervised Learning, Data Processing, Dataflow, Data Pipelines, MLOps (Machine Learning Operations), Big Data, Data Transformation, Artificial Neural Networks, Deep Learning, Applied Machine Learning, Performance Tuning

  • Status: Preview

    Skills you'll gain: MLOps (Machine Learning Operations), Google Cloud Platform, DevOps, Application Lifecycle Management, Applied Machine Learning, Continuous Deployment, Machine Learning, Automation, Continuous Integration, Containerization, Data Processing

  • Status: Free Trial

    Skills you'll gain: Feature Engineering, MLOps (Machine Learning Operations), Prompt Engineering, Google Cloud Platform, Generative AI, Tensorflow, Keras (Neural Network Library), Apache Airflow, Cloud Infrastructure, CI/CD, Data Pipelines, Systems Design, Cloud Platforms, Data Management, Data Governance, Hybrid Cloud Computing, Workflow Management, Artificial Intelligence, Machine Learning, Cloud Computing

  • Skills you'll gain: Generative AI, MLOps (Machine Learning Operations), Continuous Monitoring, Predictive Modeling, Data Validation, Responsible AI, Google Cloud Platform, System Monitoring, Machine Learning Methods

  • Status: Preview

    Skills you'll gain: CI/CD, MLOps (Machine Learning Operations), Apache Airflow, Data Pipelines, Google Cloud Platform, Tensorflow, Kubernetes, Metadata Management, Applied Machine Learning, Machine Learning Methods, Scikit Learn (Machine Learning Library), Containerization, Data Processing

  • Skills you'll gain: Generative AI, Continuous Monitoring, Google Cloud Platform, MLOps (Machine Learning Operations), Predictive Modeling, Data Validation, Machine Learning, Responsible AI, Artificial Intelligence and Machine Learning (AI/ML), Data Quality

What brings you to Coursera today?

Leading partners

  • Google Cloud
  • Duke University
  • Whizlabs
  • DeepLearning.AI
  • Microsoft
  • H2O.ai
  • Amazon Web Services
  • CertNexus