excellent

clear an

Great

good

good

C

The course was very informative but the slides were a little boring. The content could have been more engaging. Sometimes the supplementary reading contained examples that could have been better explained in a video. I would have appreciate a more comprehensive explanation of content on slides using markers or pointers. Sometimes I did not know where I needed to focus. I hope the instructors create more videos for the same content. This is may be because I am more of a visual or an engaged learner.

Did like the inclusion of music or sound effects in the lectures. I get the trying to be creating, but I couldn't hear the content and it was really jarring and distracting for me. I have an acquired brain injury and sudden sound is a big trigger for me.

This course wasn't as well laid out in terms of chunking down the information and the quizzes were far apart especially in the EDA section. Great info overall and learned a lot but the layout and format were a bit frustrating.

I thought the course could have provided some more concrete examples and hands-on data analysis scenarios. It was too theoretical/experimental for the business application I would put to use. The instructor does a good job of explaining his thought process, but I lost applicability about halfway through.

If only the course lasted a little bit longer... for those who wish to complete the course as soon as possible, this is the course you should take otherwise i personally find it hard to get the idea of what really "managing data analysis" means other than its basic concepts and models/ trends etc.

Good knowledge but Dr Chan's lectures become very abstract and hard to grasp, because its a lot of theory. I would have appreciated if he conducted his lectures with live examples of each concept. infact, more case studies/examples would be been effective approach.

Content could have been boiled down to about 3 lectures. Most of it was common sense. The high level over view of the life cycle of data analysis projects was interesting and overall this was a good introduction to the field.

Too theoretical. The lecturer shares a lot of knowledge and documents the course in good, well-structured text. But it's all too theoretical and not really engaging seeing the same lecturer just reading the theory.

It would be nice to have listed points or tables to summarise/compare context.

As well, it would be good to introduce example separately rather than mixing with the explanation of subject.

If you are not extremely careful, Professor Peng will absolutely deflate your enthusiasm towards data science. That is as pleasant as I can be. Otherwise it's good learning material.

Didn't get much into the managerial aspect of a data analysis. Instead, it covered best practices for conducting a data analysis. Not the same thing and a little disappointment.

It is quite general, I liked the examples, although there could be more varied examples from many other dissimilar disciplines.

The questions can get a little too wordy. Find the questions difficult to follow after reading the entire length.

I think these courses need to be condensed into a single one as the contents are rather limited individually.

will like more examples detail to understand the plots more interpretation instead generation examples

Good baseline - might be hard to follow for someone who has not been working the DS Specialization

Too theoretical for my needs but gives a good background to how to approach analytics.

too much time between the videos and the related questions to the videos

Lecture component not as concise or well edited as expected.

The course is good, but too general and a little boring :(