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。
热门 MLOps 课程和认证
DeepLearning.AI
您将获得的技能: Responsible AI, LLM Application, Large Language Modeling, Google Cloud Platform, MLOps (Machine Learning Operations), Model Deployment, Kubernetes, Model Evaluation, Software Versioning, Supervised Learning
您将获得的技能: MLOps (Machine Learning Operations), Data Preprocessing, AWS SageMaker, Model Evaluation, Model Deployment, Artificial Intelligence and Machine Learning (AI/ML), Amazon Web Services, Predictive Modeling, Machine Learning, Supervised Learning, Data Transformation, Unsupervised Learning, Classification Algorithms
您将获得的技能: Model Deployment, Large Language Modeling, Cloud Deployment, Data Ethics, CI/CD, Transfer Learning, Model Evaluation, Performance Tuning
Duke University
您将获得的技能: 机器学习, Python 编程, MLOps（机器学习运营）, 数值分析, 应用编程接口 (API), Pandas（Python 软件包）, 命令行界面, 面向对象编程（OOP）, 数据结构, 测试自动化, 调试, 模型部署, 软件测试, 数据导入/导出, 数据操作, NumPy, 脚本
Duke University
您将获得的技能: MLOps（机器学习运营）, 云计算, DevOps, 集装箱化, 模型评估, 云部署, Microsoft Azure, 微软 Azure, GitHub, Docker (软件), 模型部署, 迁移学习, 拥抱的脸, CI/CD, Model Evaluation, Transfer Learning, 机器学习软件
Google Cloud
您将获得的技能: 数据建模, Google Cloud 平台, 数据处理, 数据存储技术, 数据管理, MLOps（机器学习运营）, Data Management, 模型部署, 应用机器学习, 功能工程
您将获得的技能: Model Deployment, Data Preprocessing, Model Evaluation
您将获得的技能: MLOps (Machine Learning Operations), Model Deployment, CI/CD, Continuous Deployment, Docker (Software), Kubernetes, Containerization, AI Workflows, Scalability, AI Orchestration, DevOps, Model Evaluation, Continuous Monitoring, Version Control
Duke University
您将获得的技能: 机器学习, 功能工程, MLOps（机器学习运营）, 数据分析, 探索性数据分析, Microsoft Azure, Python 编程, 云部署, 模型评估, 数据预处理, 模型部署, 无服务器计算, 数据管道, 微软 Azure, 云平台, Model Evaluation, Amazon Web Services, AWS SageMaker
Duke University
您将获得的技能: 生成式人工智能, 计算机编程, 云计算, 大型语言建模, DevOps, 集装箱化, 詹金斯, 自然语言处理, 命令行界面, Docker (软件), 无服务器计算, 拥抱的脸, CI/CD, 应用程序部署, Amazon Web Services, 恢复性应用程序接口, 数据管道, 拉斯特（编程语言）, 法学硕士申请, 测试案例
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
Pragmatic AI Labs
您将获得的技能: Model Deployment, MLOps (Machine Learning Operations), Hugging Face, Rust (Programming Language), Cloud Deployment, Application Deployment, CI/CD, Performance Tuning, Large Language Modeling, Performance Testing, Cross Platform Development, Cryptography
总之，以下是 10 最受欢迎的 mlops 课程
- LLMOps: DeepLearning.AI
- AWS: Machine Learning & MLOps Foundations: Whizlabs
- Advanced Deployment, MLOps, and Generative AI in Azure: Packt
- 面向 MLOps 的 Python 基本知识: Duke University
- MLOps 工具：MLflow 和拥抱脸: Duke University
- 使用 Vertex AI 进行机器学习操作 (MLOps)：管理功能: Google Cloud
- DevOps to MLOps Bootcamp– Build & Deploy ML Systems: Packt
- Operationalizing ML Models: MLOps for Scalable AI: Coursera
- MLOps 平台：亚马逊 SageMaker 和 Azure ML: Duke University
- Rust 编程: Duke University
