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
Skills you'll gain: MLOps (Machine Learning Operations), Model Deployment, Scalability, Model Optimization, CI/CD, Model Training, Artificial Intelligence and Machine Learning (AI/ML), Model Evaluation, Performance Measurement, Business Metrics, Verification And Validation, Performance Analysis
Skills you'll gain: Model Deployment, Software Documentation, Code Reusability, Model Training, Continuous Delivery, Test Automation, Continuous Integration, Technical Documentation, API Design, Application Programming Interface (API), Maintainability, Version Control, Package and Software Management, Code Review, Verification And Validation, Technical Writing
Pragmatic AI Labs
Skills you'll gain: MLOps (Machine Learning Operations), Databricks, Apache Spark, Model Evaluation, Hugging Face, Data Architecture, Recurrent Neural Networks (RNNs), LLM Application, Data Science, Data Mining, Mathematical Modeling, Scala Programming, Continuous Monitoring, Rust (Programming Language), Lean Six Sigma, Statistical Inference, Artificial Intelligence, Functional Testing, Exploratory Data Analysis, Programming Principles
Microsoft
Microsoft
Skills you'll gain: MLOps (Machine Learning Operations), Feature Engineering, Microsoft Azure, Model Deployment, CI/CD, Continuous Deployment, Fine-tuning, Model Training, Kubernetes, Apache Kafka, Real Time Data, Transfer Learning, AWS Kinesis, Data Architecture, Data Store, Model Evaluation, Cloud Computing, Machine Learning, Data Science, Information Technology
Skills you'll gain: MLOps (Machine Learning Operations), Istio, AI Integrations, Hybrid Cloud Computing, Model Deployment, Cloud Computing Architecture, Cloud Platforms, Feature Engineering, Kubernetes, Systems Design, Cloud Infrastructure, Generative AI, Microsoft Azure, Infrastructure as Code (IaC), Job Analysis, CI/CD, Solution Architecture, Terraform, AI Security, Cloud Security
Skills you'll gain: MLOps (Machine Learning Operations), Model Deployment, Model Training, Feature Engineering, Generative AI, Model Evaluation, Databricks, Generative Model Architectures, Model Optimization, Vector Databases, Redis, Microsoft Azure, Deep Learning, Performance Stress Testing, PyTorch (Machine Learning Library), LLM Application, Embeddings, Program Evaluation, Artificial Neural Networks, Python Programming
Skills you'll gain: Model Evaluation, Model Deployment, MLOps (Machine Learning Operations), Systems Architecture, Model Training, Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Systems Design, Machine Learning, Technical Communication, Scalability, Data Science, Personal Development
Duke University
Skills you'll gain: Rust (Programming Language), Containerization, Data Pipelines, CI/CD, Docker (Software), Jenkins, Application Deployment, DevOps, Continuous Integration, Hugging Face, Large Language Modeling, Test Case, Restful API, Serverless Computing, Generative AI, Memory Management, Command-Line Interface, Natural Language Processing, Computer Programming, Cloud Computing
Skills you'll gain: Generative AI, MLOps (Machine Learning Operations), Retrieval-Augmented Generation, Embeddings, Data Maintenance, Data Governance, Data Quality, Data Pipelines, Cloud Computing, Solution Architecture, Vector Databases, Model Evaluation, Data Validation, Technology Roadmaps, Data Analysis, Data Science, Information Technology, Continuous Monitoring, Software Versioning, Application Deployment
Skills you'll gain: MLOps (Machine Learning Operations), Google Cloud Platform, Model Deployment, DevOps, Model Evaluation, Cloud Deployment, Continuous Monitoring, Automation
Skills you'll gain: MLOps (Machine Learning Operations), Model Deployment, Google Cloud Platform, Data Store, Data Storage, Data Modeling, Data Management
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.
