MLOps Courses and Certifications

MLOps Concepts

29 ratings at DataCamp

Discover how MLOps can take machine learning models from local notebooks to functioning models in production that generate real business value.

• DataCamp
• 2 hours
• Self-Paced
• Free Trial Available

MLOps Deployment and Life Cycling

11 ratings at DataCamp

In this course, you’ll explore the modern MLOps framework, exploring the lifecycle and deployment of machine learning models.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

MLOps Fundamentals

Dive into the foundations of Machine Learning Operations (MLOps), learning the concepts of productionizing and monitoring machine learning models!

• DataCamp
• 14 hours
• Self-Paced
• Free Trial Available

Fully Automated MLOps

Learn about MLOps architecture, CI/CD/CM/CT techniques, and automation patterns to deploy ML systems that can deliver value over time.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

MLOps for Business

Learn about MLOps, including the tools and practices needed for automating and scaling machine learning applications.

• DataCamp
• 3 hours
• Self-Paced
• Free Trial Available

Credential

MLOps | Machine Learning Operations

607 ratings at Coursera

Comprehensive MLOps training covering Python, Rust, GitHub Copilot, cloud platforms, and LLMs. Gain skills for data science, ML engineering, cloud architecture, and AI product management.

• Coursera
• 24 weeks, 5 hours/week
• Self-Paced
• Paid Course
• 4 courses

MLOps for Scaling TinyML

8 ratings at edX

This course introduces learners to Machine Learning Operations (MLOps) through the lens of TinyML (Tiny Machine Learning). Learners explore best practices to deploy, monitor, and maintain (tiny) Machine Learning models in production at scale.

• edX
• 7 weeks, 2-4 hours/week
• Self-Paced
• Free Online Course (Audit)

Python Essentials for MLOps

358 ratings at Coursera

Master Python essentials for MLOps: data handling, functions, testing, Pandas, NumPy, and APIs. Gain practical skills for automating ML workflows and building robust data pipelines.

• Coursera
• 1 day 19 hours 7 minutes
• Self-Paced
• Paid Course

Cloud Machine Learning Engineering and MLOps

91 ratings at Coursera

Develop machine learning applications using cloud computing, AutoML, and MLOps. Explore emerging topics like edge ML and AI APIs. Build a Flask web app for ML predictions.

• Coursera
• 13 hours 47 minutes
• Self-Paced
• Paid Course

MLOps Tools: MLflow and Hugging Face

66 ratings at Coursera

Explore MLflow and Hugging Face for MLOps, covering model tracking, deployment, fine-tuning, and cloud integration. Gain practical skills in managing ML workflows and creating interactive demos.

• Coursera
• 1 day 1 hour 53 minutes
• Self-Paced
• Paid Course

MLOps Platforms: Amazon SageMaker and Azure ML

56 ratings at Coursera

Learn to build, train, and deploy ML solutions using Amazon SageMaker and Azure ML. Gain hands-on experience with data engineering, modeling, and MLOps on leading cloud platforms.

• Coursera
• 1 day 7 hours 9 minutes
• Self-Paced
• Paid Course

Credential

Machine Learning Operations (MLOps) on Google Cloud

496 ratings at Coursera

Master MLOps on Google Cloud by exploring the full lifecycle—feature management, model evaluation, automated workflows, and production-grade pipelines using Vertex AI and Kubeflow SDK.

• Coursera
• Self-Paced
• Paid Course
• 4 courses

Machine Learning Operations (MLOps): Getting Started

481 ratings at Coursera

Learn MLOps tools and best practices for deploying, evaluating, monitoring, and operating production ML systems on Google Cloud, enabling continuous improvement and efficient model deployment.

• Coursera
• 3 hours 32 minutes
• Self-Paced
• Paid Course

Complete MLOps Bootcamp With 10+ End To End ML Projects

3842 ratings at Udemy

End-to-End MLOps Bootcamp: Build, Deploy, and Automate ML with Data Science Projects

• Udemy
• 2 days 2 hours 46 minutes
• Self-Paced
• Paid Course

MLOps Zero to Hero

1465 ratings at Udemy

Learn Production-Grade MLOps using DVC, MLFlow, AWS, Docker, Kubernetes, KServe, SageMaker and Kubeflow.

• Udemy
• 12 hours 20 minutes
• Self-Paced
• Paid Course