This is one of the most practical Azure ML courses I’ve taken. The four modules cover the entire machine learning lifecycle, from design to deployment. The best part was learning how to set up automation using HyperDrive for hyperparameter tuning—it felt very close to real-world scenarios. The course also explained how to publish models for batch and real-time inference, which I was struggling to understand before. A solid course for both exam prep and professional growth.

This course is an excellent resource for anyone preparing for the DP-100 exam. The four modules cover everything from basics to deployment, and I particularly liked the hands-on labs with Azure ML Designer and SDK. The explanations of AutoML and HyperDrive were very clear, which helped me understand how to optimize models effectively. By the end, I felt much more confident not just about the exam but also about applying these skills in real projects at work.

 The course is very comprehensive and covers all the core topics needed for the Microsoft Azure Data Scientist certification. What stood out to me was the coverage of lifecycle management—experimenting, training, tuning, and deploying models. The AutoML and HyperDrive sections were extremely helpful since those can be tricky areas. If I had to point out one improvement, it would be to add more quizzes for practice, but overall it’s excellent preparation.

I really appreciated how structured this course was. Each module built logically on the previous one, starting from fundamentals and ending with real-time deployments. The step-by-step guidance in configuring environments and creating ML pipelines gave me a lot of practical skills. I also liked that the course used scenario-driven lessons instead of just theory. It made the learning more engaging and relatable. Definitely a must-do for DP-100 aspirants.

I enrolled in this course to prepare for the DP-100, and it has been very helpful. The lessons on SDK-based workflows gave me a lot of clarity on how to go beyond drag-and-drop tools. I especially liked the focus on scalable deployment and using production-ready compute targets. It’s not just exam prep—it actually prepares you for real-world Azure ML projects. I would definitely recommend it to data scientists working in cloud environments.

I was looking for a course that didn’t just teach theory but also walked through implementation, and this one delivered. Each module reinforced concepts with practical exercises, which helped me remember better. I particularly enjoyed the Azure ML Designer labs since they gave me a chance to quickly prototype models. By the end of the course, I felt confident about both taking the DP-100 and applying these skills at work.

Fantastic learning resource! The DP-100 course covers Azure Data Science essentials in detail, combining theory with practical labs, ensuring complete exam preparation and skill development.

Overall great class and good materials as well as the instructors were excellent. I learned a lot.

Good course

Good course

Good course

Good course

Good course

Good course

Good course

Good course

Good course

I found this course extremely helpful for DP-100 preparation. It provides hands-on labs and clear explanations of Azure ML concepts. The structure is well-paced, ensuring learners gain both theoretical and practical skills. It builds confidence in tackling real-world data science challenges while preparing thoroughly for the certification exam.

This course simplifies complex Azure Data Science concepts into easy, understandable lessons. Excellent balance between theory and practice, ensuring readiness for real-world applications and DP-100 success.

A must-have course for DP-100 aspirants. It offers in-depth coverage of Azure DS concepts, practice scenarios, and exam strategies, making certification achievement smooth and highly rewarding.