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Data Science Studies // Python/R [2018 Study Plan]

Feature

The Journey Toward Data Science: A Study Roadmap

*Pivoting from web development to data analytics*

~4,000
Pages
10
Months
~442
USD Certifications
3
Fountain Pens
Section I

Career Pivot

It's time to start studying again, and I've decided against pursuing .NET/Web Programming in favor of Data Science. I've only begun researching what I need to learn to get better acquainted with Data Science, and for now, I will focus on Python Programming.

I'm already pretty good with SQL and Relational Databases (SQL Server, Oracle), but there's much more to explore. Beyond Math and Statistics, I want to understand how to work with unstructured data.

 

Section II

Subject List

My initial study list (subject to change as I learn what I need) includes the following topics, presented in no particular order:

  • →Python Language — foundational programming for data tasks
  • →R Language — statistical computing and graphics
  • →MongoDB / NoSQL — working with non-relational data structures
  • →Big Data — understanding Hadoop and Hive
  • →Cloud Tools — leveraging Amazon S3

Additionally, I will need to brush up on my Math and Statistics skills, as it has been a few years since university.

Section III

Reading Estimate

  • →Volume — 4,000 Pages [5 to 6 books, each 500 to 800 pages]
  • →Timeline — 10 months [100 pages per week] // Estimated Completion Time: October 2018
Section IV

Resources

Python
  • →Intro to Python, 5th Edition — Mark Lutz
  • →Programming in Python — Mark Lutz
R
  • →The Art of R Programming — Matloff
Section V

Certifications

There are several certifications available for Python and R to serve as a measuring stick and pace-setter.

CertificationFocusCost
70-773Big Data w/ Microsoft R$165 USD
98-381Intro to Python$127 USD
MongoDB DBAAssociate Level$150 USD
Certifications are not my primary goal; rather, they serve as a measuring stick and pace-setter.
Section VI

Updates

Update (12/13/17) - Python

I am currently studying the 5th Edition of Learning Python by Mark Lutz. It is a larger volume with 40 chapters. I am taking my time and have read about 10 chapters over 17 days. I will try to pick up the pace as I delve deeper into this book and hope to finish it by mid-January 2018.

The content in this book is substantial; I've already filled out a 70-page notebook and had to re-ink three fountain pens. At this rate, I will need three more notebooks. Writing out the code manually helps me grasp it better and allows me to see differences, such as lists versus dictionaries.

Update (5/30/18) - Art of R Programming

I purchased The Art of R by Matloff and am currently studying it. I have installed R Studio on my i7 Windows 10 and i3 Linux systems.

Update (11/11/18) - Study Statistics First

This process is taking longer than anticipated. I have completed textbooks for both Python and R. Now, I am focusing my efforts on studying statistics itself rather than just tools or platforms. I aim to improve and hone my analytical mindset first, then augment it with the necessary tools.

  

Documenting the transition from programmer to data scientist.

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