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
您将获得的技能: AI Enablement, Cloud Development, Large Language Modeling, Image Analysis, AI Workflows, Feature Engineering, Cloud Services, Applied Machine Learning, Computer Vision, MLOps (Machine Learning Operations), Artificial Intelligence, Transfer Learning, Model Deployment, Generative AI, Natural Language Processing, Data Integration
Google Cloud
您将获得的技能: Feature Engineering, Data Preprocessing, Tensorflow, Data Pipelines, MLOps (Machine Learning Operations), Keras (Neural Network Library), Statistical Methods, Data Transformation, Data Modeling, Machine Learning
Google Cloud
您将获得的技能: Data Preprocessing, MLOps (Machine Learning Operations), Workflow Management, AI Workflows, Data Governance, Data Management, Model Deployment, Data Lakes, Google Cloud Platform, Model Evaluation, Tensorflow, Data Pipelines, Machine Learning, Feature Engineering, Data Transformation
您将获得的技能: Google Cloud Platform, Generative AI, MLOps (Machine Learning Operations), Applied Machine Learning, Model Deployment, Tensorflow, AI Workflows, Artificial Intelligence, Cloud Infrastructure, Machine Learning, Natural Language Processing
您将获得的技能: Model Deployment, Generative AI, Data Wrangling, Project Planning, Data Preprocessing, Responsible AI, Data Governance, Exploratory Data Analysis, Applied Machine Learning, Large Language Modeling, AI Enablement, MLOps (Machine Learning Operations), Data Science, Prompt Engineering, Model Evaluation, Feature Engineering
状态：免费试用您将获得的技能: Google Cloud Platform, Artificial Intelligence and Machine Learning (AI/ML), Responsible AI, Artificial Intelligence, Data Quality, Cloud API, Applied Machine Learning, Model Deployment, Machine Learning, MLOps (Machine Learning Operations), Business Intelligence, Natural Language Processing
状态：新状态：免费试用您将获得的技能: AWS SageMaker, AWS Kinesis, Amazon Redshift, Cloud Security, MLOps (Machine Learning Operations), Amazon S3, Amazon CloudWatch, AWS Identity and Access Management (IAM), Model Deployment, Real Time Data, Feature Engineering, Data Storage, Data Security, Encryption, Key Management
状态：免费试用您将获得的技能: Statistical Modeling, Microsoft Azure, Statistical Methods, Data Science, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, MLOps (Machine Learning Operations), Azure Synapse Analytics, Cloud Computing, Data Preprocessing, Data Management, Model Deployment, Model Evaluation, Development Environment
状态：预览Google Cloud
您将获得的技能: Google Cloud Platform, CI/CD, Apache Airflow, MLOps (Machine Learning Operations), Data Pipelines, Tensorflow, Model Deployment, Metadata Management, AI Workflows, AI Orchestration, PyTorch (Machine Learning Library), Containerization
状态：新您将获得的技能: Docker (Software), CI/CD, Model Deployment, Cloud Deployment, Cloud Development, Application Performance Management, Google App Engine
状态：预览您将获得的技能: MLOps (Machine Learning Operations), Model Deployment, Google Cloud Platform, Data Governance, Data Management, AI Workflows, Predictive Modeling, Machine Learning, Data Pipelines, Feature Engineering, Model Evaluation, Performance Tuning
您将获得的技能: Generative AI, MLOps (Machine Learning Operations), Google Cloud Platform, Tensorflow, Model Deployment, AI Workflows, Artificial Intelligence, Applied Machine Learning, Machine Learning, Model Evaluation, Feature Engineering, Natural Language Processing, Supervised Learning
总之，以下是 10 最受欢迎的 mlops 课程
- H2O Cloud AI Developer Services: H2O.ai
- Feature Engineering - 한국어: Google Cloud
- Machine Learning in the Enterprise - 日本語版: Google Cloud
- Introduction to AI and Machine Learning on GC - 简体中文: Google Cloud
- Data Science and Machine Learning H2O.ai Platforms: H2O.ai
- Innovating with Google Cloud Artificial Intelligence - 日本語版: Google Cloud
- AWS: ML Workflows with SageMaker, Storage & Security : Whizlabs
- Azure ML: Explore & Configure the Machine Learning Workspace: Whizlabs
- ML Pipelines on Google Cloud - 日本語版: Google Cloud
- Data Science Model Deployments and Cloud Computing on GCP: Packt
