Best MLOps Certifications and Courses to Look for in 2024: Both Paid and Free

MLOps, a combination of machine learning (ML) and operations (Ops), has become an essential skill for professionals aiming to bridge the gap between developing machine learning models and deploying them in production. As the demand for MLOps expertise grows, various online platforms offer certifications and courses to help you gain the necessary skills. Here’s a comprehensive guide to the best MLOps certifications and courses available in 2024, including both paid and free options.

Paid Certifications and Courses

1. Google Cloud Professional Machine Learning Engineer

• Platform: Google Cloud
• Cost: $200 for the exam; preparation courses vary in price.
• Description: This certification validates your ability to design, build, and productionize ML models using Google Cloud technologies. The exam covers ML best practices, model development, and MLOps practices.
• Ideal For: Professionals with experience in Google Cloud and ML who want to demonstrate their expertise in deploying and maintaining ML models in production.

2. AWS Certified Machine Learning — Specialty

• Platform: Amazon Web Services (AWS)
• Cost: $300 for the exam; preparation courses vary in price.
• Description: This certification is designed for individuals who perform a development or data science role. It validates your ability to build, train, tune, and deploy ML models on AWS.
• Ideal For: ML engineers and data scientists who use AWS for their ML workflows.

3. Azure Machine Learning Engineer Associate

• Platform: Microsoft Azure
• Cost: $165 for the exam; preparation courses vary in price.
• Description: This certification focuses on designing and implementing an Azure AI solution, including machine learning, computer vision, natural language processing, and knowledge mining.
• Ideal For: Professionals working with Azure who want to specialize in MLOps practices.

4. Coursera — Machine Learning Engineering for Production (MLOps) Specialization

• Platform: Coursera (Offered by DeepLearning.AI and Andrew Ng)
• Cost: $49 per month (financial aid available)
• Description: This specialization consists of four courses covering foundational MLOps concepts, model deployment, monitoring, and continuous integration/continuous delivery (CI/CD) pipelines.
• Ideal For: Individuals looking for a comprehensive, hands-on introduction to MLOps from a highly respected authority in ML education.

5. Udacity — Machine Learning DevOps Engineer Nanodegree

• Platform: Udacity
• Cost: $399 per month
• Description: This nanodegree program covers building and deploying ML pipelines, CI/CD for ML, model versioning, and orchestration. It includes real-world projects and mentorship.
• Ideal For: Those seeking an in-depth, project-based learning experience with personalized support.

Free Certifications and Courses

1. IBM — MLOps Fundamentals

• Platform: IBM Skills Network (Coursera)
• Cost: Free (with optional paid certificate)
• Description: This course covers the basics of MLOps, including versioning, reproducibility, continuous integration, and continuous delivery of ML models.
• Ideal For: Beginners looking to get an introduction to MLOps concepts and practices.

2. Google Cloud — MLOps: Continuous Delivery and Automation Pipelines in ML

• Platform: Coursera (Audit for free)
• Cost: Free to audit; certificate available with a paid subscription.
• Description: This course teaches you how to build and orchestrate ML pipelines on Google Cloud, covering CI/CD for ML and automation best practices.
• Ideal For: Anyone interested in learning MLOps practices using Google Cloud, without the need for a certification.

3. Microsoft — Azure AI Fundamentals

• Platform: Microsoft Learn
• Cost: Free
• Description: This learning path provides an introduction to AI and MLOps, covering Azure Machine Learning, model deployment, and monitoring.
• Ideal For: Beginners and those new to Azure, looking to understand the basics of AI and MLOps.

4. Kaggle — MLOps: From Model Deployment to Model Management

• Platform: Kaggle
• Cost: Free
• Description: This course on Kaggle covers the end-to-end MLOps process, from model deployment to monitoring and management.
• Ideal For: Data scientists and ML engineers looking for a practical, hands-on introduction to MLOps.

Conclusion

As MLOps continues to gain traction in the industry, acquiring skills in this area can significantly enhance your career prospects. Whether you prefer paid courses with certifications or free courses to get started, there are plenty of options available in 2024 to suit your needs and budget. Investing time in these courses will not only bolster your resume but also equip you with the tools and knowledge to excel in the evolving field of machine learning operations.