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.
42credentials
2online degrees
170courses

Results for "mlops (machine learning operations)"

  • Universidad de los Andes

    Skills you'll gain: Social Network Analysis, Systems Thinking, Unsupervised Learning, Data Storytelling, Risk Analysis, Computer Vision, Deep Learning, Reinforcement Learning, Financial Statement Analysis, Predictive Modeling, Project Management Life Cycle, Time Series Analysis and Forecasting, Marketing Analytics, MLOps (Machine Learning Operations), Simulations, Descriptive Analytics, Matplotlib, Exploratory Data Analysis, Verification And Validation, Natural Language Processing

    Earn a degree

    Degree · 1 - 4 Years

  • Universidad de los Andes

    Skills you'll gain: Real-Time Operating Systems, Supervised Learning, Semantic Web, LangChain, Unsupervised Learning, Cloud-Native Computing, Continuous Deployment, Computer Vision, Reinforcement Learning, Natural Language Processing, Deep Learning, Cost Estimation, Biomedical Engineering, MLOps (Machine Learning Operations), Artificial Intelligence, Data Ethics, Game Theory, Linear Algebra, Machine Learning Methods, Responsible AI

    Earn a degree

    Degree · 1 - 4 Years