DW
Condense but solid course on ML basics. AND first time I was guided in a cloud provider for ML use cases without having to shed tears from frustration. Very good to gain first familiarity with Azure.

Machine learning is the foundation for predictive modeling and artificial intelligence. If you want to learn about both the underlying concepts and how to get into building models with the most common machine learning tools this path is for you. In this course, you will learn the core principles of machine learning and how to use common tools and frameworks to train, evaluate, and use machine learning models. This course is designed to prepare you for roles that include planning and creating a suitable working environment for data science workloads on Azure. You will learn how to run data experiments and train predictive models. In addition, you will manage, optimize, and deploy machine learning models into production. From the most basic classical machine learning models, to exploratory data analysis and customizing architectures, you’ll be guided by easy -to-digest conceptual content and interactive Jupyter notebooks. If you already have some idea what machine learning is about or you have a strong mathematical background this course is perfect for you. These modules teach some machine learning concepts, but move fast so they can get to the power of using tools like scikit-learn, TensorFlow, and PyTorch. This learning path is also the best one for you if you're looking for just enough familiarity to understand machine learning examples for products like Azure ML or Azure Databricks. It's also a good place to start if you plan to move beyond classic machine learning and get an education in deep learning and neural networks, which we only introduce here. This program consists of 5 courses to help prepare you to take the Exam DP-100: Designing and Implementing a Data Science Solution on Azure. The certification exam is an opportunity to prove knowledge and expertise operate machine learning solutions at cloud scale using Azure Machine Learning. This specialization teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring in Microsoft Azure . Each course teaches you the concepts and skills that are measured by the exam.

DW
Condense but solid course on ML basics. AND first time I was guided in a cloud provider for ML use cases without having to shed tears from frustration. Very good to gain first familiarity with Azure.
MA
The journey was really interesting. I'm really inspired to go on this course till its end.
SA
This course is very easy to understand and have a great value for new data science professionals. To the point explanations and engaging content by team Microsoft.
FM
Good course with a focus on helping the learner to better understand ML concepts and the coding associated to it before diving deep into Azure tool
SS
Very good content and explanations by the instructor
SH
I found this course very intellectual and practical in learning machine learning and deep learning.
LD
The course is really effective in providing material that will reinforce the learning process; audio learning, hands-on labs, visual learning, quizzes, and final review test.
NG
Awesome course and instructor was great in delivering content
JK
Great course with lots of insights. Definetly worth it!
GM
some answers are wrong in 4th course. Rest of the course was very comprehensive and a must do before dp100.
SC
Really annoying and very hard authentication puzzle where you have to identify matching items 15 times. I want to learn, not spend my time doing stupid authentication puzzles.
ML
Using Microsoft Azure was optional. Other than that, we get a refreshener on ML topics with great examples.