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: Model Evaluation, Generative AI, Continuous Monitoring, MLOps (Machine Learning Operations), Model Deployment, Machine Learning Methods, Applied Machine Learning
您将获得的技能: MLOps (Machine Learning Operations), Model Deployment, Test Data, Model Evaluation, Data Synthesis, Development Environment, Claims Processing, Performance Tuning, Applied Machine Learning, Computer Hardware
您将获得的技能: Model Evaluation, Generative AI, Continuous Monitoring, Google Cloud Platform, Responsible AI, MLOps (Machine Learning Operations), Predictive Modeling
您将获得的技能: Model Evaluation, MLOps (Machine Learning Operations), Generative AI, Continuous Monitoring, Google Cloud Platform, Predictive Modeling, Responsible AI, Data Quality
KodeKloud
您将获得的技能: MLOps (Machine Learning Operations), Apache Kafka, Apache Airflow, Apache Spark, Extract, Transform, Load, Data Lakes, Data Pipelines, Distributed Computing, Real Time Data, DevOps, Big Data, Data Preprocessing, Feature Engineering, Model Deployment, CI/CD, Pandas (Python Package), Data Transformation
Google Cloud
您将获得的技能: Model Evaluation, Generative AI, Google Cloud Platform, MLOps (Machine Learning Operations), Predictive Modeling, Continuous Monitoring
您将获得的技能: Model Evaluation, Generative AI, Model Deployment, MLOps (Machine Learning Operations), Google Cloud Platform, Continuous Monitoring, Responsible AI
您将获得的技能: Model Deployment, MLOps (Machine Learning Operations), Generative AI, Dependency Analysis, Dashboard, Application Deployment, Continuous Deployment, System Monitoring, Responsible AI, Performance Tuning, Site Reliability Engineering, Release Management, Kubernetes, Application Performance Management, CI/CD, Performance Analysis, Continuous Monitoring, Automation, Cloud Platforms, Data-Driven Decision-Making
您将获得的技能: MLOps (Machine Learning Operations), LLM Application, AI Security, Test Automation, Test Driven Development (TDD), Code Coverage, Unit Testing, CI/CD, Continuous Integration, Testability, Large Language Modeling, Model Deployment, Responsible AI, Maintainability, AI Workflows, Scripting, Software Engineering, Python Programming, Statistical Analysis, SQL
您将获得的技能: MLOps (Machine Learning Operations), Continuous Integration, Artificial Intelligence and Machine Learning (AI/ML), DevOps, Service Level Agreement, API Design, Performance Measurement, Performance Analysis
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
您将获得的技能: Responsible AI, Data Ethics, Model Deployment, AI Product Strategy, Technical Design, Prompt Engineering, AI Security, Artificial Intelligence and Machine Learning (AI/ML), Model Evaluation, Technical Communication, Communication, AI Workflows, MLOps (Machine Learning Operations), LLM Application, Apache Airflow, System Design and Implementation, Python Programming, CI/CD, SQL, AWS CloudFormation
总之，以下是 10 最受欢迎的 mlops 课程
- Machine Learning Operations (MLOps) with Vertex AI: Model Evaluation - Español: Google Cloud
- ML Model Development and Tracking: Hands-on Guide: KodeKloud
- MMachine Learning Operations (MLOps) with Vertex AI: Model Evaluation - 한국어: Google Cloud
- Machine Learning Operations (MLOps) with Vertex AI: Model Evaluation - Français: Google Cloud
- Data Engineering Essentials: KodeKloud
- Machine Learning Operations (MLOps) with Vertex AI: Model Evaluation - Português Brasileiro: Google Cloud
- Machine Learning Operations (MLOps) with Vertex AI: Model Evaluation - Bahasa Indonesia: Google Cloud
- Deploying and Maintaining Production AI Systems: Coursera
- Testing and Refining LLM Applications: Coursera
- Deploy & Optimize ML Services Confidently: Coursera
