Statistics with Python

I agree. Depends on the long term goal. FYI to OP. https://www.coursera.org/specializations/statistics-with-python

Every Data Science Masters math prerequisite is at least college-level course or equivalent knowledge in:

1. Multivariate Calculus
2. Linear algebra
3. Probability/Statistics

But, UMSI MADS has no such prerequisite. I even wrote them an email to make sure, they responded nope, you don't have to know any of that, except what is in their Statistics with Python Coursera specialization.

I wonder how's that possible because from what I've read, these math skills are essential if you wanna be a good Data Scientist?

Because if they publish the price, it would probably mean less clicks though the ad network they are using to monetize those posts (I mean that site, not Coursera). As with most specializations in Coursera, the price is U$D 49 per month, and there are 3 courses in this specialization.

Here's the link to the course:

https://www.coursera.org/specializations/statistics-with-python

The price is shown when you click the "Enroll" button.

ahhh sure, self learning statistics was the best thing I did as a hobby. I don't know about your use case(professional or hobbyist) and how much time you have on hand , but what I did was after learning the basic python libraries numpy , matplotlib from the coursera specializations and youtube I mentioned in main thread , I took some break from learning and answered as much quality question as possible on stack overflow related to data analysis(was good for my numpy, matplotlib, seaborn and also my ego coz my reputation was increasing :) )and started a visualization blog.Although it wasn't necessary it helped me a lot and I had enough time. I didn't know R till then , and I started this stats book by Andy Field as I wanted more of application and somewhat less of mathematical derivations(ISLR is good too). It is in R , but I studied the theory portion from it and implemented all its code in Python by myself and doing a lot of research. After completing this 1000 page book in Python , I understood python is good for ml and data science but R is best when it comes to stats.I am presently arranging all the python code I learnt and did while doing this book to push on github both in R and Python(it's wonder no one has redone this book in python).

So , tl;dr ,I did this specialization , and then read Andy Field's R book.And I referred to kaggle and fivethirtyeight along with other sites sometimes for datasets and articles.

I was referring to a couple courses specifically for the exam prep. They are private courses that you get invited to after applying, about 2 months before the latest that you can take the exam (you bet I milked it).

For review content, UMich has a statistics with python specialization, but the exam just uses a calculator. I found Basic Statistics by University of Amsterdam more appropriate for preparing for the exam.

Thank you! On that note, how do you think that broad Python program compares against this program and this program?

Sorry for all these questions!

I am also interested in learning more about using Python for statistical analysis.

Has anyone out there completed the Coursera/UofMichigan Statistics w/ Python Specialization course?

I recently wrote a couple of short stats programs for a class that performed ANOVA and Linear Regression analyses using scipy.stats, stats.f_oneway, scipy.stats.linregress.

I used as a reference just to look up how to use a couple of functions the following websites:

Scipy Lecture Notes and Real Python

there is a statistics course on R made by duke university, you can watch it for free by auditing it

https://www.coursera.org/specializations/statistics

statistics with python by Michigan university

https://www.coursera.org/specializations/statistics-with-python

just uses python
here's a 3 course specialization on python and statistics from the university of michigan
https://www.coursera.org/specializations/statistics-with-python

and here's one on python and statistics for financial analysis from The Hong Kong University of Science and Technology
https://www.coursera.org/learn/python-statistics-financial-analysis

read this book
Think Stats
Think Stats is an introduction to Probability and Statistics for Python programmers.

https://greenteapress.com/wp/think-stats-2e/

Coursera has a lot of courses you can audit for free. It's not too expensive to get a handful of certifications if you want those, but the certifications themselves are probably not worth it.

For R:

Data Science

Advanced Statistics for Data Science

For Python:

Statistics

Applied Data Science

Other Languages:

Excel, Tableau, MySQL

SAS

Here are a couple places to start:

1. This free stats textbook is an OK introduction and is also not very theoretically rigorous: https://www.openintro.org/stat/textbook.php?stat_book=os
2. Intro to Statistical Learning w/ Applications in R (commonly known as "ISLR): also freely available online, will teach you the basics in very broad strokes + applications to machine learning/data science. Much of the theory is glossed over in favor of examples + applications: http://faculty.marshall.usc.edu/gareth-james/ISL/
3. UMich has a free stats course available on Coursera in Python. I haven't taken it, but it looks to be a decent intro from the contents (the other ones on Coursera are taught in R, which I imagine will be less useful in the OMSCS context). https://www.coursera.org/specializations/statistics-with-python
4. For something more in-depth, MIT has a series of 5 courses on edX: https://www.edx.org/micromasters/mitx-statistics-and-data-science
5. If you really want to learn statistics at a graduate level, you can take a look at Casella & Berger's "Statistical Inference," which is the classic inference text (and iirc includes 3-4 chapters on probability theory). It's probably much more in-depth than you would need for OMSCS, but if you intend to get this deep you should read this before you read ISLR/other things.

If you want to learn "probability" specifically, I'd start w/ the Casella/Berger. Probability theory is a subset of statistics but probably won't be the focus of any OMSCS courses (which would be much more regression/inference focused).

It seems that your comment contains 1 or more links that are hard to tap for mobile users. I will extend those so they're easier for our sausage fingers to click!

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Esse é o case.

Eu estou estudando no momento Python por essas fontes aqui (essa, essa e essa).

Eu também estou realizando esse curso. E quando terminar esses pretendo começar esses aqui (1, 2, 3 e 4) eu digo que pretendo, pq já fiz o pedido de auxilio financeiro do courseira só estou esperando aprovação.

Fora isso eu tenho alguns livros aqui comigo de algebra linear, matematica discreta e estatistica que foram bastante recomendados e eu baix.. aluguei na loucadora do Paulo Coelho, e eu estou acompanhando um curso de estatistica da USP.

São todos cursos gratuitos, mas estou curtindo bastante, especialmente esses do Coursera que parace ter um projeto aplicado para portfólio.

Mas digo que estou estudando isso a 1 mês mais ou menos, mas as coisas ainda não clicaram comigo ainda não.