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
2online degrees
170courses

Results for "mlops (machine learning operations)"

  • Status: New

    Skills you'll gain: Jupyter, MLOps (Machine Learning Operations), Google Cloud Platform, Virtual Machines, Machine Learning, Development Environment, Collaborative Software

  • Skills you'll gain: Data Ethics, Responsible AI, Applied Machine Learning, MLOps (Machine Learning Operations), Machine Learning, Software Visualization, Data Integrity, Artificial Intelligence

  • Status: Preview

    Skills you'll gain: Prompt Engineering, Google Gemini, Multimodal Prompts, Generative AI, Generative Model Architectures, Application Lifecycle Management, AI Product Strategy, Prototyping, MLOps (Machine Learning Operations), LLM Application, Google Cloud Platform

  • Skills you'll gain: Big Data, Analytics, Data Analysis, Applied Machine Learning, MLOps (Machine Learning Operations), Google Cloud Platform, Machine Learning, Predictive Modeling, SQL

  • Skills you'll gain: Responsible AI, Data Ethics, Artificial Intelligence, Google Cloud Platform, MLOps (Machine Learning Operations), Machine Learning, Data Quality

  • Skills you'll gain: Google Cloud Platform, Data Lakes, Metadata Management, Taxonomy, MLOps (Machine Learning Operations)

  • Skills you'll gain: Predictive Analytics, Big Data, Predictive Modeling, Advanced Analytics, Analytics, Applied Machine Learning, Google Cloud Platform, MLOps (Machine Learning Operations), Data Analysis, Machine Learning Methods, Data Modeling

  • Status: New

    Skills you'll gain: Google Gemini, Generative AI, Responsible AI, Google Cloud Platform, AI Product Strategy, Data Governance, Cloud Infrastructure, Cloud Computing Architecture, Decision Making, MLOps (Machine Learning Operations), Business

  • Skills you'll gain: Responsible AI, Data Ethics, Artificial Intelligence, Google Cloud Platform, Open Source Technology, Artificial Intelligence and Machine Learning (AI/ML), MLOps (Machine Learning Operations), Data Quality

  • Status: New

    Skills you'll gain: Jupyter, MLOps (Machine Learning Operations), Google Cloud Platform, Artificial Intelligence and Machine Learning (AI/ML), Data Analysis

  • Universidad de los Andes

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

  • Skills you'll gain: Social Network Analysis, Systems Thinking, Unsupervised Learning, Data Storytelling, Deep Learning, Reinforcement Learning, Computer Vision, Time Series Analysis and Forecasting, Predictive Modeling, Project Management Life Cycle, Marketing Analytics, Portfolio Management, MLOps (Machine Learning Operations), Strategic Decision-Making, Exploratory Data Analysis, Descriptive Analytics, Simulations, Random Forest Algorithm, Data Cleansing, Operations Research