MLOps Courses
MLOps courses focus on the practices and tools for managing machine learning projects throughout their lifecycle. You can learn about model deployment, monitoring, and version control, along with how to streamline collaboration among teams. Topics often include automation techniques and the integration of machine learning into operational workflows.
Popular MLOps Courses and Certifications
DeepLearning.AI
Skills you'll gain: Responsible AI, LLM Application, Large Language Modeling, Google Cloud Platform, Model Training, MLOps (Machine Learning Operations), Fine-tuning, Version Control, Supervised Learning
Amazon Web Services
Skills you'll gain: Model Evaluation, MLOps (Machine Learning Operations), Amazon Web Services, Model Deployment, Machine Learning
Edureka
Skills you'll gain: MLOps (Machine Learning Operations), DevOps, CI/CD, Continuous Integration, Application Deployment, Kubernetes, System Monitoring, Data Preprocessing, Applied Machine Learning, Version Control, Machine Learning, Machine Learning Methods, Docker (Software), Containerization, Artificial Intelligence and Machine Learning (AI/ML), Scikit Learn (Machine Learning Library), Statistical Machine Learning, Machine Learning Algorithms, Apache Kafka, Amazon Web Services
Duke University
Skills you'll gain: Pandas (Python Package), MLOps (Machine Learning Operations), NumPy, Model Deployment, Data Manipulation, Test Script Development, Software Testing, Data Import/Export, Test Automation, Python Programming, Code Reusability, Debugging, Data Structures, Machine Learning, Scripting, Application Programming Interface (API), Command-Line Interface
Skills you'll gain: MLOps (Machine Learning Operations), Containerization, AI Workflows, Model Deployment, LangGraph, Agentic Workflows, Artificial Intelligence and Machine Learning (AI/ML), CrewAI, BeeAI, Docker (Software), Cloud Deployment, Agentic systems, Google Cloud Platform, Cloud Platforms, Kubernetes, Scalability
Skills you'll gain: MLOps (Machine Learning Operations), Model Deployment, Model Training, Data Collection, Data Management, Model Evaluation, Data Preprocessing, Automation
Skills you'll gain: MLOps (Machine Learning Operations), API Design, CI/CD, Software Quality Assurance, Code Review, Maintainability
Duke University
Skills you'll gain: Fine-tuning, MLOps (Machine Learning Operations), Model Deployment, Cloud Deployment, Hugging Face, Containerization, CI/CD, Docker (Software), Microsoft Azure, Continuous Deployment, Cloud Computing, Machine Learning Software, GitHub
Skills you'll gain: MLOps (Machine Learning Operations), Model Deployment, CI/CD, Continuous Deployment, Docker (Software), Kubernetes, Containerization, AI Workflows, Scalability, Continuous Monitoring
Skills you'll gain: MLOps (Machine Learning Operations), Model Deployment, Data Modeling, Google Cloud Platform, Data Store, Data Management, Data Storage Technologies, Data Import/Export
Board Infinity
Skills you'll gain: MLOps (Machine Learning Operations), Model Deployment, LLM Application, Application Deployment, Model Training, AI Workflows, AI Security, Retrieval-Augmented Generation, Scalability, CI/CD, Model Evaluation, Containerization, Continuous Monitoring, Software Versioning, Incident Response
Skills you'll gain: Model Deployment, Application Deployment, Data Preprocessing, Model Optimization
How to choose the right MLOps course
Start with your goal. If you want to implement MLOps for production machine learning models, look for courses covering model deployment strategies, CI/CD pipelines for ML, and monitoring ML models in production. If you want to use specific tools like Kubeflow or MLflow, choose courses that cover setup, configuration, and best practices for those tools.
