學生對 华盛顿大学 提供的 大规模数据处理：系统与算法 的評價和反饋

This course totally reminds me of some courses back in college: unorganized material and the assignments are unrelated to the tutorial. The assignments themselves seem to be very helpful but the tutorials did no help of achieving these assignments.

I had a hard time following the instructor despite that I've completed all the certificate for python from University of Michigan. I'm aware of my background of python is still not strong enough so I thought it's probably just me not able to learn it fast enough.

But then I watched the tutorial about SQL. As a data architect / ETL developer, SQL is something I'm familiar with and use it everyday and then I realized that the instructor couldn't explain a nested query well. The reason I was able to understand about the SQL part is because I already know.

Lost in details. Professionals(btw I hold a MSc degree in Computer Engineering) cannot get anything from this. What is the point of writing frequency.pl where there is a hist() function in R? If the instructor is trying to teach us how to program in any language, then I can assure you the data science class is not the right place. I recommend the instructor check ESSEC Business School for analytics subject to better comprehend the Coursera and its goals.

The course info makes no mention of Python as a prerequisite. Yet the first assignment demands Python knowledge and skills. Without which you can't pass the assignment. Yet the week's lecture is not about Python.

The instructors do not respond and they provide computer programs that do not work. They are aware that there are issues in the programs but have done nothing to remedy the issue.

Th first three classes are very 'thin' in content and the assignments are easy. The fourth class is basically optional and it has TONS of content. What's the point?

Outdated, unintelligibly exercises, terrible lectures.

Poorly designed videos, too long and confused

very poor!