28-AUG-2021: Created for first session of python 16 week!
Python 2 suggested resources & coding norms
Eric uses these three books extensively to learn and teach Python. Paper copies are coming back wth gusto! Run after the bandwagon!
Deitel Python for CS and Data Science
Intro to Python for Computer Science and Data Science by Paul Deitel; 1st Edition (2020), Pearson; ISBN-10: 0-13-540467-3
Expensive, wretched publisher, but current and comprehensive of neato high level data analytics libraries.
The beast: Lutz's Learning Python
Learning Puython by Mark Lutz; 5th Edition (2013), O'Reilly; ISBN: 978-1-449-35573-9
Super cheap, great publisher, the most exhaustive "out there" about why and hows of python components. A little heavy.
Loeliger and McCullough's Git book
Version Control with Git by Jon Loeliger & Matthew McCullough; 2nd Edition (2012), O'Reilly; ISBN: 978-1-449-31638-9
Cheap, great publisher, with conceptual overviews of git internals which demystifies the errors and syntax
Eric Recommends you use jupyter-notebook which is part of the anacaonda package. So please install the Anaconda Individual Edition free suite of open source tools to a local system, preferably in the long run, a system running OSx or Linux, but Windows will do just fine.
Note that linked in learning has reviews of these skills.
All CCAC students have free access to linkedIn learning via the my.ccac.edu portal. Navigate to this portal, loggin in if necessary. Then use the find feature in your browser, usually Control + F to search for the word "linked". This will navigate you to linkedIn learning's login portal. Enter your @acd.ccac.edu email address and you should be granted system access.
wb_incandescentHierarchy of Resources
official docs & library references
send any object or type.method to dir() or help() and read the official comments for the actual code you're invoking. This can also be browsed at python.org
The Lutz and Deitel are our official "good books". Python is so hot now, there are gobs of books that are severely lacking in completeness and accuracy. Reader beware!
Extract the topic you believe you wanter to learn more about, and serach for that TERM in a non-archiving search engine. Avoid the crutch of typing a problem-specific question into a search engine, hoping that the gods will deliver an answer into your lap, relieving your brain of its worrisome task.