Excellent course materials, especially the videos, with content that is thoughtfully composed and carefully edited. Very good python training, great instructors, and overall great learning experience.
Great course to learn the basics! The supplementary material in Jupyter notebooks is extremely valuable. Really appreciate the PhD students who took the time to explain even the simplest of codes :)
创建者 Amarildo Q
•Excelente!
创建者 Kondapalli S V
•wonderfull
创建者 Andria
•Very nice.
创建者 Beatriz J F
•Excellent!
创建者 Yiyi Z
•wonderful
创建者 madhurima c
•very good
创建者 Yurgenis R
•very good
创建者 Satrio T S
•Excellent
创建者 DR. S
•AMAZING!
创建者 Nedal
•v
e
r
y
g
o
o
d
创建者 Gabriel A A C
•Excelent
创建者 Israel F
•Amazing
创建者 周晓
•Thanks!
创建者 KAYDAN P R
•awssem
创建者 Frank S Y R
•Nice!
创建者 Chang L
•good
创建者 GUNDA S K G
•good
创建者 ATHIPATLA S N
•nice
创建者 BODIREDDI S A
•nice
创建者 PUPPALA B A
•GOOD
创建者 PEDASINGU T K
•gud
创建者 Jerrold
•There are two main fields of study in this course which forms the foundation for the specialization: statistical theory, and programming with python data analysis packages. I learned so much about statistics and visualization that would have taken months to learn in university, I gained a lot of experience and knowledge from this course. I have a decent background in Jupyter notebook from university yet I still learned many new things and got an excellent chance to practice programming in the python packages. The course offered excellent optional practices and gave us several extremely insightful and educational analysis reports done in JN that were related to the module of the week for us to download.
I recommend you have a datacamp subscription to have access to some extra notes regarding programming in the packages particularly Pandas to get the most out of this course by attempting all the optional programming practices.
创建者 Luis D R T
•I loved several things, first that gives you an overview, useful, clear and fun of several basic statistical concepts such as measures of central tendency, different forms of graphic representation, and one of the most important at least for me (already that neither in school nor I would have ever thought about) the types of sampling that exist, because in school there is usually something called simple random sampling and we develop statistical techniques for it, almost completely ignoring the other types of sampling that are really common in real life and that when we face them we don't panic, I know that this is an easy level and I appreciate that in some way, but I would have expected a more difficult course that would have made the concepts really stay in me because I would be thinking about them continuously and how to apply them to the tasks that are presented week by week
创建者 Matteo L
•I think the content here is great and gives you a good overview for understanding and visualizing data without getting into the mathematics. Week 4 is absolutely great in terms of how the information is conveyed by Mr. West who is an excellent teacher in my opinion. I do think, however, that the quizzes and notebook assignments could be a little bit more challenging and I would have loved to have answers to the "more practice" notebooks. I think it would have been great for those notebooks to have been part of the assignments, adding to the difficulty of the course.
创建者 Iver B
•Good introduction to basic statistical methods with an emphasis on working with surveys, and a good introduction to basic statistical techniques with core Python, numpy, matplotlib, seaborn and statsmodels. Instructors and presentations are excellent, very clear. I would give it five stars if it were more interactive, i.e. with more in-video quizzes, and practice quizzes between videos. Also, I wish I had take this course before I did the Applied Data Science with Python specialization, also on Coursera, but, alas, it wasn't available then.