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.
38credentials
1online degree
166courses

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Results for "mlops (machine learning operations)"

  • Status: Free Trial

    Skills you'll gain: Prompt Engineering, Databricks, Large Language Modeling, LLM Application, Generative AI, Performance Analysis, Apache Airflow, Workflow Management, Amazon Bedrock, Data Lakes, ChatGPT, Extract, Transform, Load, OpenAI, Multimodal Prompts, MLOps (Machine Learning Operations), AWS SageMaker, Performance Tuning, Scalability, Database Management Systems, Generative Model Architectures

  • Status: Free Trial

    Skills you'll gain: Predictive Modeling, Responsible AI, Predictive Analytics, Machine Learning, Data Ethics, MLOps (Machine Learning Operations), Applied Machine Learning, Data-Driven Decision-Making, Statistical Modeling, Performance Measurement, Supervised Learning, Business Ethics, Decision Tree Learning, Artificial Intelligence and Machine Learning (AI/ML), Leadership and Management, Business Analytics, Data Science, Machine Learning Algorithms, Artificial Intelligence, Data Processing

  • Status: Free Trial

    Skills you'll gain: MLOps (Machine Learning Operations), Application Deployment, Containerization, CI/CD, Docker (Software), Microsoft Azure, Cloud Computing, Cloud Applications, Machine Learning Software, GitHub, Application Programming Interface (API)

  • Status: Free Trial

    Alberta Machine Intelligence Institute

    Skills you'll gain: Supervised Learning, Feature Engineering, Responsible AI, Machine Learning Algorithms, Data Ethics, Applied Machine Learning, Data Quality, Data Processing, MLOps (Machine Learning Operations), Jupyter, Data Validation, Machine Learning, Business Operations, Data Cleansing, Product Lifecycle Management, Machine Learning Methods, Ethical Standards And Conduct, Classification And Regression Tree (CART), Test Data, Project Management

  • Status: Free Trial

    Skills you'll gain: Feature Engineering, MLOps (Machine Learning Operations), Responsible AI, Prompt Engineering, Google Cloud Platform, Generative AI, Tensorflow, Dataflow, Keras (Neural Network Library), Data Quality, Exploratory Data Analysis, Machine Learning Methods, Machine Learning, Applied Machine Learning, Data Pipelines, Apache Airflow, Scikit Learn (Machine Learning Library), Data Cleansing, Real Time Data, Cloud Computing

  • Status: New
    Status: Free Trial

    Skills you'll gain: Exploratory Data Analysis, Data Collection, Data Ethics, MLOps (Machine Learning Operations), Feature Engineering, Data Cleansing, Responsible AI, Applied Machine Learning, Data Analysis, Solution Design, Statistical Analysis, Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Predictive Modeling, Application Deployment, Generative AI, Continuous Monitoring

  • Status: Free Trial

    Duke University

    Skills you'll gain: MLOps (Machine Learning Operations), Responsible AI, Artificial Intelligence and Machine Learning (AI/ML), PyTorch (Machine Learning Library), Containerization, Tensorflow, Web Frameworks, Rust (Programming Language), Microsoft Copilot, DevOps, Cloud Solutions, CI/CD, Machine Learning, Serverless Computing, Docker (Software), GitHub, Command-Line Interface, Big Data

  • Status: Free Trial

    Skills you'll gain: AWS Kinesis, AWS SageMaker, Machine Learning Algorithms, Data Collection, Amazon Redshift, MLOps (Machine Learning Operations), Image Analysis, Reinforcement Learning, Amazon Web Services, Scalability, Forecasting, Feature Engineering, Algorithms, Machine Learning, Technical Design, Data Analysis, Real Time Data, Predictive Modeling, Applied Machine Learning, Data Modeling

  • Status: Preview

    Skills you'll gain: MLOps (Machine Learning Operations), Data Modeling, Google Cloud Platform, Feature Engineering, DevOps, Data Processing, Data Management, Applied Machine Learning, Data Storage

  • Status: Free Trial

    Skills you'll gain: AWS SageMaker, MLOps (Machine Learning Operations), Microsoft Azure, Exploratory Data Analysis, Data Pipelines, Amazon Web Services, Feature Engineering, Cloud Solutions, Cloud Engineering, Artificial Intelligence and Machine Learning (AI/ML), Data Analysis, Applied Machine Learning, Machine Learning Methods, Serverless Computing, Amazon S3, Machine Learning, Machine Learning Algorithms, Python Programming

  • Status: Free

    Skills you'll gain: MLOps (Machine Learning Operations), AWS SageMaker, Amazon Web Services, Machine Learning, Applied Machine Learning, Predictive Modeling

  • Status: Free Trial

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

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