Probability and Statistics in Data Science using Python
University of California, San Diego via edX

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Overview
The job of a data scientist is to glean knowledge from complex and noisy datasets.
Reasoning about uncertainty is inherent in the analysis of noisy data. Probability and Statistics provide the mathematical foundation for such reasoning.
In this course, part of the Data Science MicroMasters program, you will learn the foundations of probability and statistics. You will learn both the mathematical theory, and get a handson experience of applying this theory to actual data using Jupyter notebooks.
Concepts covered included: random variables, dependence, correlation, regression, PCA, entropy and MDL.
Taught by
Alon Orlitsky
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Reviews
1.9 rating, based on 28 reviews

Anonymous is taking this course right now.
IF you work full time and don't already have a MS or PhD in mathematics/computer science I feel that this course will be too time consuming to complete. Run away. I really tried to like this course, but in the end I feel I have learned little and been... 
Ronny De Winter completed this course, spending 7 hours a week on it and found the course difficulty to be medium.
This review was written after finishing 7 of the 10 sessions. The schedule is unreliable, with many delays (3 weeks of delay after 7 weeks). This is a boring course, too many mathematical proofs, with longwinded videos and dull scholarly examples with... 
Anonymous completed this course.
If you do not have time to kill, I would give you a friendly advice to choose other courses on probs and stats. The lecture videos are pretty lengthy, some even reaching an hour, only for you to eventually realize that there is a disconnect between what... 
I just finished this course as part of the UCSD Micromasters Program in edX so I just battled through it (spending ~1520 hours/week studying). Otherwise I probably would've given up. Nevertheless, in spite (or because) of the challenging nature of the...

Anonymous completed this course.
I really cannot recommend this course at all. For somebody with the required prerequisite background stated by the instructors, I felt no where near qualified to understand most of the content. It is extremely heavy on mathematics, which is what I expected.... 
Anonymous completed this course.
I have received a passing grade on the course and finished 9 out of 10 weeks now on the verified track (10th week is not available now due to a delay, which is very typical for majority of the weeks on first iteration of this class). I have to say the... 
Anonymous is taking this course right now.
This course is way too long for a 10 week 10 hours per week course. This is as a lot of the seminars are over 15 minutes long and some are 27 minutes long with a lot of incoherent mumbling/off topic rambling. A lot of times the assignments were difficult... 
I'm extremely frustrated with this course. I had already familiarized myself with the concepts such as probability and statistics before I took the course, and I thought this course would take me to a deeper level but I was WRONG! Instead, I ended up...

Anonymous completed this course.
The content is not engaging at all, video lessons are much too long (more than 1 hour per topic) and 80% of the time is spent with mathematical proofs instead of real world application examples. This creates a huge disconnect from the lecture and the... 
Anonymous is taking this course right now.
Almost near finishing the course with securing 59% out of 60% before the final exam which counts as 40% with overall passing grade required of 65%. Feedback on the course: 1) Poorly designed course 2) Lack practical application knowledge hence i am quite... 
Anonymous completed this course.
This course goes right to the basics of statistics in incredibly fickle detail that means that it takes a lot more than the 10 hours a week that is suggested. The course due to detail and length of presentation would be better if it were 2 or 3 separate... 
I was stuck having to complete this course to finish the micromasters path but be advised, do not take this class unless you absolutely have to! I've heard that the Harvard micromasters in DS content is MUCH better but have not experienced it myself. The...

Anonymous is taking this course right now.
This course is awful. The lecture material does not give you a good understanding of the material and you will have to go to other sources (youtube etc.) to figure out how to answer the questions on the problem sets. You will also need to spend upwards of 20 hours/week instead of the 1012 hours/week claimed by this course.
The programming assignments are also nonintuitive and could be handled much better.
There are much better ways of handling a course like this and I am severely disappointed with this course. 
Anonymous is taking this course right now.
I posted the following message in this class today. Unless you have a solid background in math and have nothing else to do, then do not take this class. I agree with the other negative comments. I have been developing/teaching college/university classes,... 
Anonymous is taking this course right now.
I am 3/4 way through the whole course. I'd like to provide some feedback. First of all, I don't mind a statistics and probability course should provide proof for many theorem or concepts. I think it's well done that the professor can add proof into the... 
Anonymous completed this course.
A BIG Thank you to Professors of this course Alon Orlitsky & Yoav Freund & TAs! This is the most interesting course on Probability and Statistics for Data Science compared to similar courses on Coursera, Udacity and Udemy. Its been a great course with... 
I do NOT recommend this course. I have an engineering and math background and found this course to be very time consuming and difficult. There is a large disconnect between what is taught in the course videos and the problems set given at the end of each...

I have taken mathematical statistics and several other probability, stochastic process course, inference, before. So Maybe I am more prepared than other students complaining here. I spend about 7 hours each week for this course. The difficulty level is medium (5 in 110 scale) for me, at least, much less Multiple integrals of 2 variables than mathematical statistics. The lectures cover a lot of materials. If somebody comes with a weaker preparation, eg, only takes from an probability/regression for economics, it may take much more time (I guess 20 hours a week?) to finish this course.

Anonymous is taking this course right now.
Course takes way longer than the suggested 1015 hours per week for 10 weeks, and is probably closer to 30 hours. The lecturer has a very old and outdated style of teaching, which feels very bland and plain making it difficult to follow the lectures for a long period of time. The problems have a varying level of difficulty, and some of them require knowledge of future videos to complete. I have wasted so much time trying to answer a question, only to realise i could've answered it easily if I had gone ahead and watched future lectures.

The teaching is really bad, the examples used are really easy to missunderstand  Wondering if the teachers know what they're talking about.. Lots of complaints inside the "Probability and Statistics in Data Science using Python" wiki.