Best YouTube Channel to Learn MLOPS
Best YouTube Channel to Learn MLOPS
(1) Krish Naik
Krish Naik is a legend in the data science industry who comes from a non-CSE background, making his journey all the more inspiring.
He began his career as a developer and, like many, explored different career paths. He appeared for competitive exams like GATE and UPSC but didn’t succeed there. However, these setbacks helped him discover his true passion—data science.
From that moment on, Krish never looked back. He’s now one of the most trusted mentors in the field of data science and machine learning. His teaching style is simple, practical, and extremely effective, helping thousands of learners build successful careers.
Among his most valuable yet underrated contributions is his MLOps series on YouTube. Despite admitting in an interview that people generally don’t show much interest in learning MLOps, he still uploaded the entire series.
He believed that even if only a few people benefited from it, it would be worthwhile. This selfless attitude reflects his commitment to education. His MLOps series is incredibly detailed and hands-on, covering everything from CI/CD to model deployment and monitoring.
It’s a must-watch for anyone serious about becoming a machine learning engineer. The content bridges the gap between model development and real-world implementation, which is exactly what companies look for today.
Even beginners can follow and implement the concepts with ease. Krish Naik didn’t just teach data science—he made it accessible and career-defining.
(2) CampusX
Similarly, CampusX, founded by Nitish Singh, is another powerhouse in the data science community.
An electrical engineer by background, Nitish’s journey into data science is both impressive and motivating. Despite not having a traditional computer science education, he mastered complex concepts and now shares them with clarity and passion.
He is more than just a content creator—he is a genuine mentor. Nitish is especially known for his insightful videos on MLOps, a critical yet often ignored aspect of ML. In 3–4 detailed videos, he breaks down the need for MLOps in today’s industry.
One standout is his 45-minute analogy that explains, in simple terms, why MLOps is not just useful but necessary. He illustrates how companies today are seeking professionals who can manage the full machine learning lifecycle—from data preprocessing and model building to deployment and monitoring.
Nitish highlights the increasing demand for engineers who understand reliability, scalability, and maintainability, all of which are central to MLOps. His content is packed with real-world examples, and his calm, insightful teaching style makes learning feel effortless.
He doesn’t create content for the sake of views—he genuinely wants learners to succeed. Nitish Singh is undoubtedly an underrated legend in the data science and ML space.
If you’re aiming to master machine learning end-to-end, his videos provide the depth and clarity that most others miss. With mentors like him, the journey into data science becomes both practical and inspiring.
(3) Vikas Das
Hi, I just wanted to mention something I recently found out about — Vikas Das has put up a full MLOps course, and trust me, it’s a goldmine if you are serious about Data Science and wish to become industry-ready. The one thing that makes this course stand out is the fact that he begins absolutely from scratch. I mean, even from Git basics, Docker, DVC (Data Version Control), MLflow, to even fundamental concepts like Object-Oriented Programming,everything is covered.
Every lecture is incredibly detailed, with most being over 2 hours long. There’s even a 3-hour one on creating a full pipeline! And not just the duration — it’s the depth and the simplicity he imparts that really make the content stand out.
What I specifically adore about Vikas Das is that he’s not only a content producer,he’s actually working in the field. So the things he teaches are what’s actually being used in real-life projects. He brings that practical perspective that a lot of other creators tend to miss out on. It’s different from folks like Krish Naik and Nitish Singh ,don’t get me wrong, they’re both great educators and I’ve learned a lot from them too. But because they’re no longer working in the industry full-time, a little of their content does come across as a bit academic or slightly outdated relative to the rapidly changing MLOps world.
All that being said, I actually think it’s a fantastic idea to go through the advanced MLOps course material by Krish and Nitish — they have done a brilliant job setting the stage. But after going through that, sure, skip on over to Vikas Das’ channel. You’ll get that added oomph from someone who’s working on actual problems on a daily basis in production environments.
If you want to level up your skillset and learn how things really work in the world, this course is well worth your time.
(4) Vizura
Recently, I discovered a YouTube channel called “Vizura”, and honestly, it’s one of the best channels I’ve come across for Artificial Intelligence and Machine Learning. The quality of teaching and depth of explanation truly stand out from the crowd. The instructor behind Vizura is an IIT graduate who completed his PhD at MIT, which already tells you the kind of academic excellence and research mindset he brings to the table. But what really impressed me is not just his credentials — it’s how effortlessly he breaks down complex AI and ML concepts into simple, easy-to-understand lessons.
Unlike most channels that jump straight into coding or use superficial explanations, Vizura starts from absolute scratch and gradually builds your understanding step-by-step. Whether it’s linear regression, neural networks, or deep learning architectures, every topic is explained conceptually first and then implemented practically, so you truly understand what’s happening behind the scenes. The instructor has a calm, structured, and insightful teaching style that keeps you engaged throughout.
Another thing I love about this channel is how it blends theory, mathematics, and practical coding in a balanced way — something most tutorials fail to achieve. It’s perfect for both beginners and professionals who want to strengthen their fundamentals in AI and ML.
If you’re genuinely serious about mastering artificial intelligence, I strongly recommend checking out Vizura. The content looks extremely promising, and I believe it has the potential to become one of the top AI/ML learning resources on YouTube.
(5) Sunny Savita
I recently came across Sunny Savita, and I must say he’s one of the finest instructors in the field of MLOps. He is a Computer Science graduate with deep domain expertise in Artificial Intelligence, Machine Learning, and Generative AI. What truly sets him apart is his ability to explain even the most complex MLOps concepts in a way that’s both clear and practical. His teaching style reflects a perfect balance between theory and hands-on implementation, making it ideal for learners who want to truly understand how things work in real-world AI systems.
The best thing about Sunny Savita’s MLOps course is the level of detail he goes into. He doesn’t just talk about high-level topics — he dives deep into everything, from logger files and exception handling to data pipelines, model training, and deployment. He covers the entire lifecycle of an ML project with exceptional clarity. The course also includes more than 20 hours of in-depth content, which is quite comprehensive for anyone serious about mastering MLOps.
What I personally admire most is how he connects all the dots — showing not only how to build and deploy models, but also how to structure a professional-level ML project like it’s done in the industry. His explanations are logical, organized, and practical, making complex DevOps and ML concepts much easier to follow.
If you’re planning to learn MLOps from scratch or enhance your current knowledge, I truly believe Sunny Savita is one of the best instructors available online for this domain.
Final Conclusion on the Best YouTube Channel to Learn MLOPS
We really hope that you have liked this article very much. Kindly, please share it with your friends and family too.