Add DS links.

Author: Proto

00_overview.ipynb

@@ -10,6 +10,14 @@
    "source": [
     "# Welcome to Intro to Python!\n",
     "\n",
+    "About Data Science\n",
+    "\n",
+    "Data science is about extracting information from sets of data. It's about scientific analysis of databases. You can also think of it as a mix of programming and analytics since data scientists will frequently use coding and other tools for their work. These things go hand in hand and any given data scientist can have one or both of those skillsets. It's not uncommon for software engineers or data analysts to be data scientists.\n",
+    "\n",
+    "Data Analytics: https://www.youtube.com/watch?v=_HbjsNaUJ2A\n",
+    "\n",
+    "There are two things required for any data science to happen: collection of data and processing that data into organized information.\n",
+    "\n",
     "There's a ton of ground to cover but here's what you should get from this course:\n",
     "\n",
     "* A quick list of terminal commands to use with our python skills\n",

readme.md

@@ -12,9 +12,10 @@ Traditional study tools can be pretty indispensable. You should take your good s
 
 __Resources for Practice__
 - [Python the Hard Way][1]: This is an extremely repetitive FREE book. And that's what makes it a fantastic learning tool.
-- 
+- [Python Fundamentals][2]: Great resource comes with all sample scripts that you can download and play with for yourself!
 
 [1]: https://learnpythonthehardway.org/book/intro.html
+[2]: https://newcircle.com/bookshelf/python_fundamentals_tutorial/index
 
 ## Using Jupyter
 
@@ -43,7 +44,7 @@ Important methods and functions:
 * set()
 * .sort()
 
-# Common Class Commands
+# Common Terminal Commands
 Windows: http://ss64.com/ps/
 Unix (Mac/Linux): http://ss64.com/bash/