Hi, I am currently mid way through this course. Prior to taking this course, I have taken the 'python for everybody' course which I found was a great course to start learning python but went less in depth as topics grew in complexity. I found that the...
Hi, I am currently mid way through this course. Prior to taking this course, I have taken the 'python for everybody' course which I found was a great course to start learning python but went less in depth as topics grew in complexity. I found that the 'Analytics in Python' class was a great course to take after 'python for everybody' because:
1) It allowed to review topics that I had already learned but with different emphasis. It for example introduces you to different libraries and teaches how to manage dates.
2) It went into more details where python for everybody was pretty light. For example I managed for the first time to do web scraping thanks to this course.
The teacher is thorough and explains things really well.
Luiz Cunha completed this course, spending 2 hours a week on it and found the course difficulty to be medium.
This course is not well constructed.
It tries to cover too many topics, without doing it properly most of the time: topics are not well or very superficially explained.
Besides the exercises/assignments need a refresh, as for some of them they don't work anymore with the unavailability of the apps API they are based on (googlemaps API, yelp API).
I completed the course as an audit learner scoring over 70%. It's a great course and the assignments are of medium level difficulty. Gives you a quick grip on Python concepts necessary for doing Data Science on unstructured data such as text. Network analysis is also presented in the course. Pandas is introduced, ML is minimal. Overall a fantastic Python Primer , nice hands on instruction.
Anonymous is taking this course right now.
The Lecturer is just way to fast and doesn't go on depth. But the quize and the project needs a lot of dept in subject to answer or complete them.