Was expecting spark based Mlib not scikit learn

Very bad notebooks/Exam. Bug in exam, instruction missing in notebook which cause it impossible to calculate the correct answer. Don't know why coursera put such un-tested, un-updated, un-reviewed course online.

Good course with good practical tasks (felt relatively simple for me, but may be more challenging for others). It's happy to see quizes as performance evaluation in comparison with peer reviews from previous specialization course. However I lack Databricks features usage and explanations (MlFlow expecially). Also Databricks runtime used during course preparation is no longer available for selection as cluster configuration - it results in different answers for specific questions (it was very painful with K-Means clustering - I just had other ordering cluster labels)

Nice course, its approach is the right mix between theory and hands-on exercise on the databricks platform...

Very practical applied machine learning course on data science while covering key components informatively

Perfect and objective content. Simple and practical exercises. I strongly recommend!

Great course for an overview but with a high level of abstraction (usage of existing libraries but very little coding of algorithms that show the details of the principles)

Well defined exercice with usage of Pyspark in Databricks