10 practical steps to Data Science.

Data Science is encompassing, broad, so broad that it sometimes seems ambiguous, making it very hard to learn.
But I came across a list of what I believe are 10 Practical Steps to learning Data Science:
1. Programming
a. Python - https://lnkd.in/gGQ7cuv
b. R - https://lnkd.in/giMGbph
c. SQL - https://lnkd.in/gM8nMNP
d. Command Line - https://lnkd.in/e3EQuis
2. Stats/Prob/Math
a. Coursera’s Statistics w/ R - https://lnkd.in/gGT9NEf
b. edX’s Probability - https://lnkd.in/gpUyC3P
c. Khan Academy Linear Algebra - https://lnkd.in/gMshbX4
3. Data Viz
a. Python Matplotlib- https://lnkd.in/gr3ifNt
b. R ggplot2 - https://lnkd.in/eThJXNr
4. Data Manipulation
a. Python Pandas - https://lnkd.in/g9kfpX4
b. R dplyr - https://lnkd.in/gAWusih
5. Machine Learning
a. Google Crash Course - https://lnkd.in/gSgkVcT
b. Stanford Coursera - https://lnkd.in/g8ZG557
c. ISLR Book - https://lnkd.in/gk8GPZC
6. Experimental Design
a. Udacity A/B Testing - https://lnkd.in/gCerh4f
7. Business Sense
a. Metrics - https://lnkd.in/gZAG7bS
8. Communication
a. Storytelling - https://lnkd.in/gwjxVUu
9. Profile Building
a. GitHub - https://lnkd.in/g4r9naJ
b. LinkedIn - https://lnkd.in/g-KHHEC
c. Kaggle - https://lnkd.in/gBC77Hu
d. DS Resume - https://lnkd.in/gU8WVAF
10. Job Search
a. Daily Expert Tips & Advice - https://lnkd.in/g8z-xXD
Hope this helps! 👍