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  • Mlops

MLOps 课程

MLOps 课程可以帮助您学习机器学习项目的部署策略、模型监控以及持续集成和交付。您可以掌握自动化工作流、管理数据管道和确保符合治理标准的技能。许多课程介绍了 TensorFlow、Kubernetes 和 MLflow 等工具,这些工具支持操作 AI Model 并简化数据科学家和 IT 团队之间的协作。


更多精彩内容:

热门 MLOps 课程和认证


  • C

    Coursera

    MLOps in R: Deploying machine learning models using vetiver

    您将获得的技能: Model Deployment, MLOps (Machine Learning Operations), Continuous Deployment, R Programming, Dashboard, Health Informatics, Applied Machine Learning, Continuous Monitoring, Predictive Modeling, Docker (Software), Application Programming Interface (API)

    中级 · 指导项目 · 不超过 2 小时

  • D

    Duke University

    管理机器学习项目

    您将获得的技能: 模型评估, 数据收集, 数据管理, Data Management, 技术解决方案, 数据预处理, 模型部署, 数据科学, 人工智能和机器学习(AI/ML), 机器学习, MLOps(机器学习运营), 项目管理生命周期, 数据清理, 市场机遇, 系统设计, 项目管理, 数据质量, 数据管道, 应用机器学习, 技术管理, 软件开发方法

    4.8
    评分, 4.8 星,最高 5 星
    ·
    352 条评论

    初级 · 课程 · 1-3 个月

  • C

    Coursera

    Automate, Evaluate and Deploy ML Models Confidently

    您将获得的技能: MLOps (Machine Learning Operations), Model Deployment, Scalability, CI/CD, Continuous Deployment, Application Deployment, DevOps, Artificial Intelligence and Machine Learning (AI/ML), Model Evaluation, Continuous Integration, Performance Measurement, Business Metrics, Process Optimization, Verification And Validation, Automation, Key Performance Indicators (KPIs), Performance Analysis, Data-Driven Decision-Making

    高级设置 · 课程 · 1-4 周

  • G

    Google Cloud

    Machine Learning Operations (MLOps): Getting Started - Español

    您将获得的技能: MLOps (Machine Learning Operations), Model Deployment, Google Cloud Platform, Cloud Management, Application Lifecycle Management, DevOps, Model Evaluation, Cloud Deployment, AI Workflows, Continuous Deployment, Continuous Integration, Automation

    中级 · 课程 · 1-4 周

  • P

    Packt

    LLM Engineer’s Handbook

    您将获得的技能: Retrieval-Augmented Generation, Large Language Modeling, Hugging Face, MLOps (Machine Learning Operations), OpenAI, Prompt Engineering, Model Deployment, AWS SageMaker, Extract, Transform, Load, Embeddings, Data Pipelines, CI/CD, Vector Databases, Model Evaluation

    初级 · 课程 · 1-3 个月

  • C

    Coursera

    Databricks Machine Learning Fundamentals

    您将获得的技能: Model Deployment, Databricks, MLOps (Machine Learning Operations), Apache Spark, Applied Machine Learning, PySpark, Data Preprocessing, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Scikit Learn (Machine Learning Library), Feature Engineering, Application Deployment, Model Evaluation, Real Time Data, Exploratory Data Analysis, Engineering

    中级 · 课程 · 1-4 周

  • C

    Coursera

    Secure AI Model Deployments & Lifecycles

    您将获得的技能: Model Deployment, MLOps (Machine Learning Operations), AI Security, Cloud Deployment, DevOps, CI/CD, Artificial Intelligence and Machine Learning (AI/ML), System Monitoring, Software Versioning, Data-Driven Decision-Making

    中级 · 课程 · 1-4 周

  • W

    Whizlabs

    Azure ML: Deploying, Managing, and Experimenting with Models

    您将获得的技能: Model Deployment, Responsible AI, Microsoft Azure, MLOps (Machine Learning Operations), Data Management, Cloud Management, Cloud Deployment, Applied Machine Learning, Model Evaluation, Scalability, Data Preprocessing, Machine Learning, Performance Tuning, Feature Engineering, Machine Learning Algorithms

    高级设置 · 课程 · 1-4 周

  • C

    Coursera

    Automate ML Pipelines for Peak Performance

    您将获得的技能: MLOps (Machine Learning Operations), Feature Engineering, Workflow Management, Predictive Modeling, Scalability, Performance Tuning

    中级 · 课程 · 1-4 周

  • M

    Microsoft

    MLOps and responsible AI practices

    您将获得的技能: Responsible AI, MLOps (Machine Learning Operations), Azure DevOps, Generative AI, Microsoft Azure, Model Deployment, AI Workflows, CI/CD, Version Control, Data Ethics, Artificial Intelligence, Model Evaluation, Git (Version Control System), Automation, System Monitoring, Continuous Monitoring

    中级 · 课程 · 1-4 周

  • C

    Coursera

    ML Production Systems

    您将获得的技能: Model Deployment, Unit Testing, MLOps (Machine Learning Operations), Test Driven Development (TDD), Software Testing, Scalability, Dashboard, Feature Engineering, Continuous Integration, Kubernetes, Scikit Learn (Machine Learning Library), CI/CD, Performance Tuning, Tensorflow, Python Programming, Software Engineering, PyTorch (Machine Learning Library), Docker (Software), Containerization, Git (Version Control System)

    中级 · 专项课程 · 1-3 个月

  • P

    Packt

    AI Engineer Professional

    您将获得的技能: MLOps (Machine Learning Operations), Convolutional Neural Networks, Recurrent Neural Networks (RNNs), Containerization, AI Workflows, Model Evaluation, Model Deployment, Generative AI Agents, LangGraph, Keras (Neural Network Library), Transfer Learning, Artificial Intelligence and Machine Learning (AI/ML), CrewAI, BeeAI, Image Analysis, Deep Learning, Large Language Modeling, Natural Language Processing, Vision Transformer (ViT), Python Programming

    高级设置 · 专项课程 · 1-3 个月

1234…35

总之,以下是 10 最受欢迎的 mlops 课程

  • MLOps in R: Deploying machine learning models using vetiver: Coursera
  • 管理机器学习项目: Duke University
  • Automate, Evaluate and Deploy ML Models Confidently: Coursera
  • Machine Learning Operations (MLOps): Getting Started - Español: Google Cloud
  • LLM Engineer’s Handbook: Packt
  • Databricks Machine Learning Fundamentals: Coursera
  • Secure AI Model Deployments & Lifecycles: Coursera
  • Azure ML: Deploying, Managing, and Experimenting with Models: Whizlabs
  • Automate ML Pipelines for Peak Performance: Coursera
  • MLOps and responsible AI practices: Microsoft

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