#
Data Science

Statistics and Machine Learning

Below are the **top discussions** from
Reddit that mention this
online Coursera specialization from
**Johns Hopkins University**.

Build models, make inferences, and deliver interactive data products.

Machine Learning Github R Programming Regression Analysis Data Visualization (DataViz) Statistics Statistical Inference Statistical Hypothesis Testing Model Selection Generalized Linear Model Linear Regression Random Forest

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Taught by

**Jeff Leek, PhD**

Associate Professor, Biostatistics

and 2 more instructors

Offered by

**Johns Hopkins University**

This specialization includes these
**5 courses**.

Statistical inference is the process of drawing conclusions about populations or scientific truths from data.

Brian Caffo, PhD

16 mentions

Linear models, as their name implies, relates an outcome to a set of predictors of interest using linear assumptions.

Brian Caffo, PhD

8 mentions

One of the most common tasks performed by data scientists and data analysts are prediction and machine learning.

Jeff Leek, PhD

20 mentions

A data product is the production output from a statistical analysis.

Brian Caffo, PhD

1 mentions

The capstone project class will allow students to create a usable/public data product that can be used to show your skills to potential employers.

Jeff Leek, PhD

1 mentions

#### Reddit Posts and Comments

0 posts • 50 mentions • top 3 shown below

**r/datascience**• comment

10 points • MarvelvsDC2019

Hey man I really appreciate that response. I definitely appreciate that link about SQL. I’ve def seen a lot of different courses about SQL and frankly I feel a bit overwhelmed by it so it’s good to know there’s one that I can take that will be enough to put it on my resume.

I’m actually currently taking the Data Science: Statistics and Machine Learning Specialization through Johns Hopkins on Coursera: https://www.coursera.org/specializations/data-science-statistics-machine-learning

Do you think I should drop it and just go to the one that you sent?

I’m on regression models right now. It’s been a while since I’ve done anything with econometrics so I wanted to do a refresher and also I wanted to go through all of it so I can get the certificate for the specialization.

Should I just finish up the whole thing or just transition over to Python? This specialization is purely R. I know that people have been saying that python is good but from the jobs that I’ve seen, it seems like either R and Python are preferred and people have said that these languages are very similar and that if you know one it’s easy to transition.

Someone earlier said that R’s data frame is very much like pandas and Numpy.

**r/datascience**• comment

1 points • rtayek

jh does a lot of stuff in r: https://www.coursera.org/specializations/data-science-statistics-machine-learning

**r/datascience**• comment

1 points • Waldo805

Data Science: Foundations using R Specialization

Data Science: Statistics and Machine Learning Specialization

(I'm not sure why it got removed maybe bc it was self promotion perhaps?)