Footnotes for Python Noobs

*ft = footnote followed by number and alpha extender

Additional Information in Support of Entries within
"Links for Python Noobs"

*ft_00a:  I've been blindly adding links to my Noobs page without looking to see how the webpage actually looks.

Blogger's "Compose" mode is not a true WYSIWYG (What You See Is What You Get)
It's close. But not exact.

So here, I will be adding elucidating additional information about some of the sites I'm recommending (or at least listing) on my "Links for Python Noobs" web page.

*ft_00b:    Which resources should I learn from?

Imagine a section of land upon which you want to add and grow a new set of plants or trees.

In order for the new additions to take hold, to 'stick' and to thrive, the soil must match their needs. Their roots must find and attach to connection-sustaining anchor points.

It's the same for making additions of new "knowledge" to your brain. New neural connections need to mate with sustaining anchor points pre-existing  in your brain's substrate. The new stuff needs to root to and stick to pre-existing anchor points. If the new material does not match and mate with such anchor points, it won't stick. It won't stay. It will flake away and be "forgotten".

That means that the best educational resources that you "learn" from should use those analogies, metaphors and vocabulary that match with pre-existing concepts already present in YOUR brain (as opposed to those present in the teacher's brain). It is your job to find those matchig resources. 

Therefore, you should sample a bunch of different candidate sources and identify the ones that best match with your personal substrate. Find the ones that have the highest "match quality" that works for you!

Some of the factors to consider include:

• Finding an inspirational teacher who gets & keeps your attention and focus
• Finding source material that activates your emotional neurotransmitters, especially dopamine (motivation to keep learning)
• Finding source content that matches your existing neural anchor points
• Encoding the presented material to attach to the anchors in your LTM (Long Term Memory)
• Strengthening the new attachements by repeated & spaced apart retreivals

An example that I am personally struggling with at the present involves how various online lecturers explain what analogy should be used when coming to grips with the concept of a "class" under Python's Object Oriented Programming (OOP) paradigm. If you are a beginner, don't try to learn that aspect now. Be patient. It will come to you eventually.

The point to make here about this thing called "class" is that many online lecturers suggest thinking of it as being a 'blueprint". Personally, for various reasons, I dislike that one. It does not match well with my personal experiences with blueprints. Thus it does not root well or make sensible neural connections for me personally. So I abandoned those sources (as applied to learning OOP) and searched for alternate teachers! They're out there if you are persistent. More specific details on that example of the match-to-learn process can be found (HERE).