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 :)
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By Debasis D•
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.
By 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
By 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.
By 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.
By Eric W•
The course in general is great for overview of basic statistics and how to display the descriptive part using charts in Python. The latter part is something new I learnt from this course. However, I rated four because there are still rooms for improvement. First, week-3 course (probability vs non-probability sampling etc.) is a bit too long and repetitive. Second, while the peer-graded assessment is interesting, I don't like to wait for my work to be reviewed, hence delaying the overall completion of my participation.
By steven h•
The course could be improved with more quizzes to apply what lectures cover. A lot of useful information is presented, but there was not enough opportunity for us to apply it. Also, the course should present more examples of statistical concepts. At times, it felt as if I was just listening to an audiobook. Statistics can be better understood by applying concepts and visualizing. Week 4, in particular, felt very rushed. There was a lot of "this will be addressed later", which diminished the relevance.
By Kuan-Chih W•
It is a fairly good course for statistics introduction. However, the explanation on how to apply with python libraries is not well-organized. Learners must have a well understanding of numpy, pandas, Matplotlib and Seaborn on their own in advance, because the TAs just read through the code without explaining why in details.
The statistics concepts lecturer is very good, but the TA didn't describe python libraries or modules selection and application concept.
By Rahul P•
Best course for Statistic to understand from Datascience POV. If you're a software developer or from computer science, then this course is good to go into to understand the statistics for DataScience.
Deducting one start for :- 1. Week 4 was too much lectures and less assignment. Felt rushed.
2. The pythonic technical tutorial was not explained much technically and hence i had to spent a lot of time on different course to learn them.
By Arfaa S•
I am so happy to learn about data visualization through python. This course gives you a good amount of insight on how to visualize data through python and helps you understand the graphs and statistics behind it. I am very thankful to the team who have made up this course as it has been very helpful to me and other students like me to be much more confident with our knowledge in Python and Statistics.
By Teodoro N I D•
The course is pretty technical and there are some gaps in the information that is presented (that will probably be addressed in later courses in the specialization), but it certainly whets one's appetite to learn more about statistics. I also appreciated the opportunities provided to apply the code that was learned and to see some of the theories in action. A worthwhile take overall.
By Divya R•
This is a tactfully curated course for getting your legs wet in statistics with python, I personally was not completely comfortable with the statistical explanation and had to refer to multiple sources but hey a splendid job in other crucial things such as working around a code!! 10/10 recommend!! I wish to connect with the tutors via Linkedin