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Online Course

Probability and Statistics in Data Science using Python

University of California, San Diego via edX

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 hands-on 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

2.0 rating, based on 21 reviews

Start your review of Probability and Statistics in Data Science using Python

  • Anonymous

    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...
  • Anonymous

    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

    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...
  • 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 long-winded videos and dull scholarly examples with...
  • Anonymous

    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

    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...
  • Anonymous

    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

    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...
  • Anonymous

    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 10-12 hours/week claimed by this course.

    The programming assignments are also non-intuitive 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

    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

    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...
  • Michael Hint completed this course, spending 15 hours a week on it and found the course difficulty to be hard.

    This course is demanding. There are 13 sections and each one has 5 to 7 videos, with each of them being up to 30+ minutes long. I did it in Audit mode (ie I didn't pay anything and didn't do the final exam in proctored mode). Given that, it is amazing...
  • Anonymous

    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

    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

    Anonymous is taking this course right now.

    Course takes way longer than the suggested 10-15 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.

  • Anonymous

    Anonymous completed this course.

    PHENOMENAL course! I took this as part of the DataScience MicroMasters on edX. One of the things I can say which might be unique is that I haven't had any math past high school Algebra. I took a little different path to a professional career (start-up) and therefore missed university. I was able to complete this with a little grit and determination. The instructors did a fantastic job covering all the concepts, with light overviews of the basics when needed. Highly suggested for those wanting to pursue Data Science careers or skills.
  • Anonymous

    Anonymous is taking this course right now.

    Wow there is a lot of content and I am struggling to be able to finish it on time. I work full time and this is definitely more work than 10 hours a week. I have knowledge of calculus and algebra from university courses, but it is still taking me a long time to complete all the tasks. I do not think I will be able to complete the course on time if I do not put in 30 plus hours a week.
  • Anonymous

    Anonymous completed this course.

    The course is great. Professors are doing their best. Other staffs also reply to questions within 1 day mostly.

    But the protocoled exam is terrible. It crashed 10min after it started. I feel all my effort was wasted only due to this terrible exam software provided by third party.
  • Anonymous

    Anonymous is taking this course right now.

    It is disapointing to spend 2 times (or more) than is informed to solve 74*(5 to 11) problem sets and use Python in less than 5% of this time.
  • Anonymous

    Anonymous is taking this course right now.

    Wow what a waste of time/money.

    Glad I am not the only one who felt there is way too much content for supposedly "10 hours per week".

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