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10 Best MLOps Courses to Learn Machine Learning

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The world of machine learning is booming, and with it comes the need for efficient and reliable ways to deploy and manage models in real-world scenarios. Enter MLOps, the bridge between data science and operations, ensuring your brilliant models don’t just gather dust but make a difference.

Choosing the right course is crucial if you’re ready to take your ML skills to the next level and become an MLOps pro. This guide will help you navigate the landscape of MLOps education and find the perfect fit for your needs.

Key Points:

What are MLOps Courses?

MLOps courses equip you with the knowledge and skills to streamline the entire machine learning lifecycle, from model development and training to deployment, monitoring, and continuous improvement. They cover topics like:

Top 10 MLOps Courses:

Here are 10 of the best MLOps courses available, catering to different learning styles and experience levels:

1. Machine Learning Engineering for Production (MLOps) Specialization

User Review: As a machine learning enthusiast who’s delved into several MLOps courses, I’d like to share my personal experiences and insights about the course, As the in-depth coverage and focus on production-ready ML systems were incredibly valuable. Andrew Ng’s expertise is evident, and the hands-on projects significantly enhanced my understanding. However, the course does expect prior knowledge of TensorFlow and Python, which could be a hurdle for complete beginners.

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2. Made With ML MLOps Course

User Review: As a machine learning enthusiast who’s delved into several MLOps courses, I have analyzed this course and can surely say that Goku Mohandas’ passion for MLOps is truly inspiring! The course structure, practical projects, and emphasis on software engineering best practices were exceptional. A bonus is that it’s completely free and open-source! However, the self-paced nature requires discipline and the ability to learn independently.

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3. MLOps | Machine Learning Operations Specialization (Microsoft)

User Review: As a machine learning enthusiast who’s delved into several MLOps courses, I’d like to say that This specialization provides a strong foundation in MLOps concepts and tools, focusing on the Microsoft Azure ecosystem. It’s ideal for those aiming to specialize in Azure MLOps. The downside is that the Azure-centric approach may need to be revised for those working with different cloud platforms.

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4. MLOps for Beginners (Udemy)

User Review: As a machine learning enthusiast who’s delved into several MLOps courses, I’d like to share my personal experience on the analysis of this course As a beginner-friendly course, it effectively introduces core MLOps concepts and tools. The affordability and hands-on exercises make it a great starting point. That being said, the content depth might feel limited compared to other options for those seeking more advanced topics.

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5. Python Essentials for MLOps (IBM)

User Review: This course excels at building a strong foundation in Python for data science and MLOps. The practical exercises and IBM’s reputation add to its credibility. The downside is that the course primarily focuses on Python skills and doesn’t delve deeply into MLOps concepts and practices.

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If you want to Level up your MLOps skills and validate your knowledge cost-free, then you can check Google’s free comprehensive certification courses.

6. MLOps Zoomcamp

User Review: This free online course offers a well-structured introduction to MLOps, covering a broad range of topics and practical projects. The live sessions and community aspect add value. However, the fast pace might be challenging for some learners, and self-discipline is required to complete the course.

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7. Practical MLOps (

User Review: The course’s emphasis on practical applications and real-world case studies is highly beneficial. It equips learners with the skills to build and deploy ML models efficiently. It’s recommended to have some prior knowledge of machine learning and deep learning to fully grasp the content.

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8. Full Stack Deep Learning

User Review: This comprehensive course covers the entire deep learning project lifecycle, including MLOps principles and best practices. The practical projects and focus on real-world applications are valuable. The course does require some foundational knowledge in machine learning and deep learning, which might be challenging for beginners.

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9. MLOps Engineering on AWS (Amazon)

User Review: This course provides a solid understanding of using AWS for MLOps tasks. It covers various AWS services and equips learners with practical skills for building and deploying ML models on the platform. The focus on AWS might limit its applicability for those working with other cloud platforms.

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10. Azure Machine Learning Engineer Associate Certification (Microsoft)

User Review: This certification program offers a structured path to validate your Azure MLOps skills and gain industry recognition. The comprehensive preparation materials and focus on real-world scenarios are beneficial. The certification requires passing an exam, which might be challenging for some learners. Additionally, the Azure-specific focus might limit its broader applicability.

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Choosing the best MLOps course depends on your individual needs and goals. Consider your current skill level, preferred learning style, and budget when making your decision. With the variety of options available, you’ll find the perfect course to launch your MLOps journey and take your machine learning skills to the next level.


The information provided in this blog post is for general knowledge and informational purposes only and does not constitute professional advice. It is essential to conduct your own research and due diligence before making any decisions related to MLOps courses or certifications.



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