MLOps for Beginners (2026) | What is MLOps? | Step-by-Step Complete Roadmap | Edureka Live
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In this video on *What is MLOps* , we will start with an overview of what MLOps is, helping participants understand its role in bridging machine learning and operations. Next, the session dives into the Key Components of MLOps, highlighting the essential elements required for successful implementation. The MLOps Lifecycle is then explored, offering insights into the stages of development, deployment, and monitoring of ML models. Attendees will also learn about the Tools & Frameworks of MLOps that enable automation and efficiency. Finally, the session wraps up by addressing the challenges of MLOps, as well as common hurdles and solutions in the journey to integrate machine learning into production systems. This structured agenda ensures a strong foundational understanding of MLOps for beginners.
✅ 00:00 - Introduction to MLOps
✅ 01:14 - What is MLOps?
✅ 01:44 - Parallel with DevOps
✅ 03:01 - Scaling AI Solution
✅ 04:55 - Challenges in Traditional ML Work
✅ 06:00 - Benefits of MLOps
✅ 07:04 - Key Components of MLOps
✅ 08:19 - MLOps LifeCycle
✅ 09:26 - Tools and Frameworks in MLOps
✅ 10:32 - Real-world applications of MLOps
✅ 11:22 - Challenges in MLOps
✅ 12:23 - Future of MLOps
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Why learn MLOps?
The aim of MLOps is to close the gap between data scientists and IT teams, ensuring speedy, reliable, and scalable deployment of machine learning models.
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Who should take up this MLOps Course?
This course is well-suited for programmers, developers, data analysts, statisticians, data scientists, and software engineers.
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What are the prerequisites for this MLOps Course?
To excel in MLOps, one must know programming languages like Python, understand ML algorithms, be familiar with deployment tools like Docker and Kubernetes, and be knowledgeable about cloud platforms.
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