The video lecture sometimes feels too fast to follow as the content in the lectures are new to the student.

The codes on the labs need updating. They don't generate the visualization necessary to reinforce learning.

good course but video explanation in not good , and his content not understandbel overall good course.....

The sited examples in this course makes the learning easily understandable. Of course, everyone likes food

Understanding Python part without having prior knowledge is confusing & led to somewhat loss of interest.

Excellent For Fundamentals on methodology, would like to learn more about Prescriptive Analytic approach.

I think some parts of the course wasn't clear enough, but by researching on google about it helped a lot.

Very good and easy to follow, although more in-depth examples of different model would have been a plus.

This course was interesting but I felt that it was slightly confusing to apply for the final assignment.

It is a bit challenging for beginners but totally worth it. Ensure you read listen to the material well.

Pretty solid information. Great for the novice with no background. Loved that it was basic and useful.

Some interactive activities like vocabulary matching may help with recall and word/process definitions.

i think this course needs more practice cases so we can get much more comfortable with the methodology

Some of the detail was briefly covered, learners need to research more from other educational sources.

Since I believe this course is an important stage of the certificate, three sections may be too short.

Un excelente marco que permite comprender el problema antes de abordar e implementar una estrategia.

More examples are needed and that the modeling programs have more comments to know what is happening

It gives a brief introduction to Data Science Methodology and explains it well with proper examples.

I enjoyed the course thoroughly but I wish more details were given for a deeper learning experience.

The methodology is good for creating a framework within which data analytics problems can be solved.

its not realy enough for experimental teaching. but it can explain the things clearly with examples

I think the final peer reviewed assignement should have more detail, more focused and not so "free"

Very detailed and instructive way to put some frame on possible future data science project to face

good as an overview. But for me it was more theoretical concepts than on hand practicing practical.

I have a unique experience to how to handle big data to find the answers to the business problems.