Learning Python starts with Learning about Learning

 

The following should be obvious to all. However, for many it's not fully obvious. Here it is:
Before we "Learn", we need to know HOW to learn. We need to know the best techniques for imprinting new stuff onto our brain's substrate, for recognizing the imprinted material at a later time and for being able to recall (pull out) the imprinted material on our own without suggestion.

A problem though, is that each of us has a strong desire to just "dive right into it". To immediately jump headfirst into the pool and swim among the intricacies of the Python computer language without concerning ourselves about planning HOW we should "learn". And more importantly, to consider what will cause us to "retain" the learnt material (imprint it into long term memory) and to understand what will enable us to later recognize and further recall at will that material as needed.

Dr, Justin Sung has a multitude of YouTube lectures about efficiently carrying out the learning process.

One of his lessons (here) identifies 6 points about proper studying techniques. Worth watching.

I don't fully agree with Dr. Sung's method of teaching because he leaves out the NeuroScience although clearly he himself knows it

A major tenant of brain science is: If it [a neural synapse] fires, it wires [it becomes a stronger connection]. Learning involves creating neural connections that stick to the cerebral cortex substrate and that stick to one another. It is possible that there are 3 trigger circuits, namely: (a) one to 'write' new material for attachment to the substrate, (b) a second one to spot written material in the form of a recognition of the material when externally re-presented to us, and (c) a third one to 'recall' the imprinted material without the aid of external suggestion. Dr. Sung's methods are directed to exercising ALL 3 circuits. He refers to imprinting as "encoding". He addresses the pre-encode filtering problem. He also suggests engaging in a form of mind mapping that aids the 3 trigger circuits.  

Using a Mind Map instead of a "Road" Map

Part of the learning process involves connecting interrelated concepts (aka interleaving) so that each stored memory fragment reinforces the storage of its adjacent fragment (and so that they all connect to a pre-existing, well memorized other memory fragment in our cortex, aka they make strong connectome linkages to the substrate and to each other)

To the right is an example of a possible such mind map.  The concept of a file stored on nonvolatile disk (or SSD) easily roots to our pre-existing understandings of computers.

Now, imagine that there is a Commas Separated Variables (CSV) text file stored on the disk. We wanted to read it in as fragments rather than to input a possibly very large file all at once. The fragments are parsed and stored in one or more Python list variables. Perhaps in a Commas Separated Variables Like Data object where the separator is a code other than a comma.

Once read into our list(s), the data is processed using string manipulation techniques. Note there is now a mind-mapped "connection" between lists and strings. The concepts are interleaved with one another.

Next, we may want to Display the processed material. I other words, it is not enough to understand list methods and string methods; we also need to tackle methods for displaying the results of out list and string manipulations.

Finally, the user reacts to the displayed material. So Keyboard and mouse activities interrelate to the list methods and the string methods. None of these concepts are islands onto themselves.

... to be continued

MORE TO EXPLORE
Mind mapping methods (Google search)
Best methods of Learning Python (Google search)
Best way to learn new material (Google search)
Archer Newton -- How to Re-Wire Your Brain
Python Programmer -- How to Remember What You Read
Huberman Lab Clips -- Top Study Habits to Improve Learning
Ultra Learning with Scott Young (a selected video spot)
--^^^-- Scott Young sample articles (here)
--^^^-- 2 Hour Interview with Scott re ULTRA-Learning (here)
Coder -- How I'm Teaching Myself Computer Science  (see his ...more materials)
MIT OpenCourseWare -- 1. Introduction to the Human Brain
--^^^-- All courses in MIT OpenCourseWare (here)
Anthony Metivier -- How to Teach Yourself (9 tips for better learning)
True Learning with ADC -- When and why you NEED to take a BREAK (from studying)
       --^^^--  more from ADC:  his Home page here and see his videos here

to be continued