Reddit reviews R for Data Science: Import, Tidy, Transform, Visualize, and Model Data

Hi /r/datascience. I'm an aspiring data scientist and I'm trying to put together a data science course that's self-taught and can be done on one's time. Any pointers would be appreciated.

Section A: Foundations in Mathematics

• Calculus I
  
  
• Calculus II
  
  
• Calculus III
  
  
• Linear Algebra
  
  
• Statistics
  
  
• Probability Theory
  
  
• Bayesian Statistics
  
  Section B: Foundations in Computer Science
  
  
• Introduction to Computer Science and Programming using Python
  
  
• Python and/or R
  
  
• SQL
  
  Section C: Basic Data Science
  
  
• Intro to Data Science
  
  Section D: Advanced Data Science
  
  
• Machine Learning
  
  
• Deep Learning
  
  These are the courses/subjects I've gathered would be most important or useful for someone trying to learn data science. Below are the resources that can be used to learn these subjects.
  
  Section A Resources
  
  Khanacademy - General Calculus, Linear Algebra
  
  PatrickJMT - General Calculus, Linear Algebra
  
  Professor Leonard - Calculus I, Calculus II, Calculus III, Statistics
  
  MIT OpenCourseWare - Single Variable Calculus (I/II), Multivariable Calculus (III), Linear Algebra, Statistics, Probability Theory/Bayesian Statistics
  
  Harvard - Probability Theory/Bayesian Statistics
  
  Section B Resources
  
  Datacamp
  
  Dataquest
  
  Codeacademy
  
  Code School
  
  LearnPython.Org
  
  Kaggle
  
  Udemy
  
  Udacity
  
  Rmotr
  
  Section C Resources
  
  University of Michigan - Introduction to Data Science in Python
  
  Harvard CS109 - Introduction to Data Science
  
  R for Data Science
  
  Section D Resources
  
  Andrew Ng's Machine Learning
  
  Jose Portilla's Python for Data Science and Machine Learning
  
  Andrew Ng's Deep Learning Series
  
  Am I missing any important courses, free or otherwise? Any important books? Any concepts I'm completely forgetting about?
  
  I've been told this is missing real education in science itself. How can I incorporate that?

What kind of resources are you looking for: books, online tutorials, cheatsheets, other?

Is there a language or technology you are specifically using or looking at using?

If you are using R I would recommend parts of Hadley Wickham's "R for Data Science: Import, Tidy, Transform, Visualize, and Model Data". Specifically the chapters on Data Import, Transformation and Tidy Data.

If you have any specific questions feel free to ask.

The chapters in question available for free online:

https://r4ds.had.co.nz/data-import.html

https://r4ds.had.co.nz/transform.html

https://r4ds.had.co.nz/tidy-data.html

To buy a physical copy of the book:

https://www.amazon.com/Data-Science-Transform-Visualize-Model/dp/1491910399/ref=sr_1_1?crid=3EQZKAWKO7ZW9&keywords=r+for+data+science&qid=1574185159&sprefix=r+for+d%2Caps%2C232&sr=8-1

Edit:

Full github repository for book source code:

https://github.com/hadley/r4ds

I used data camp and I recommend it because it covers both programming in base R and the full tidyverse library. I did the R programming course and it covered everything from functional programming to object oriented programming in R.

If you don’t want to do a monthly subscription, purchase Hadley Wickams (author of the tidyverse) book R for Data Science

Although I am not a statistician myself and given your background, some of my recommendations would be:

• All of Statistics for a concise treatment of well....all of statistics :p
  
  
• [Introduction to Statistical Learning/Elements of Statistical Learning] (https://www.amazon.com/Introduction-Statistical-Learning-Applications-Statistics/dp/1461471370/ref=sr_1_1?s=books&ie=UTF8&qid=1493070885&sr=1-1&keywords=introduction+to+statistical+learning) avaliable for free in the internet if you are interested in applying statistical methods with Machine Learning
  
  
• Introduction to Probability for a intro to probability theory which underlies most of statistics.
  
  
• One of either [Python Data Science Handbook] (https://www.amazon.com/Python-Data-Science-Handbook-Essential/dp/1491912057/ref=sr_1_1?s=books&ie=UTF8&qid=1493071026&sr=1-1&keywords=python+data+science+handbook) or [R for Data Science] (https://www.amazon.com/Data-Science-Transform-Visualize-Model/dp/1491910399/ref=sr_1_1?s=books&ie=UTF8&qid=1493071056&sr=1-1&keywords=r+for+data+science) for building programming chops in your language of choice Python or R.
  
  This should probably be enough for now but if you need more recommendations just say so :)
  
  Regarding the time series question, it's not my area of expertise but since time series analysis ends up employing many statistical methods, I think it can be considered an area of statistics (Statisticians around here correct me if I am wrong :P)

I did now. Any way of getting a sticky/wiki/FAQ of useful materials /common questions for noobs like me? People can vote/review books and MOOC's / Kaggle competitions, and what was the best for them. Give us newbies something to get started on so we don't have to flood the sticky. Then gives more of a community support rather than one person's suggestion.


For instance

Applied Predictive Modeling

or the less theory version

Intro to Statistical Learning were two books that helped me with understanding statistical models and had applications and exercises in R

R for Data Science was decent enough and had updated packages for making tidy data.


I found the Data Science Coursera Specialization decently useful, but didn't go deep enough. It did give me enough of a taste to know this is the direction I want my career to go in. So I'm hesitant to do more MOOCs.




I also don't have experience in Data Science hiring, but have it for consulting/actuarial. I'd be happy to help critique resumes during my free time for all the graduating students.

Here's the direct link to the book on Amazon.

https://www.amazon.com/Data-Science-Transform-Visualize-Model/dp/1491910399/ seems like a good one.