Python 2.7 TutorialWith Videos by mybringback.com
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About this TutorialThis is a Python 2.7 tutorial aimed at complete programming novices. Each tutorial is based on a video from the excellent "mybringback" Learn Python Programming Tutorials, complete with a summary and additional learning materials.Mybringback.com (YouTube playlist here) does an admirable job of creating simple, concise yet easy-to-understand tutorials that supply new programmers with just enough knowledge to get started. Their series fits all of the criteria I was looking for in online Python tutorials for my linguistics students, namely:
How to LearnSome of you like to be thorough and will be tempted to learn everything on each tutorial page (and the links) before moving on to next. This is akin to learning all Spanish nouns before moving on to verbs -- a noble attempt, but not a good learning strategy.
Instead, I strongly recommend learning in two passes or more. In the first pass, the goal should be to finish all of the 23 video tutorial in a relatively quick time span, while not worrying about the advanced topics and especially the "Explore" sections. (You should not, however, make it a video-watching marathon. You must try the code yourself.)
The Scope of this TutorialYou might notice that you are not building terribly exciting scripts on these tutorials. What you are doing instead is learn the basic building blocks of the Python language. Scaling up from individual pieces of programming construct to complex and structured programs that actually solve interesting problems -- such as a script that spots palindromes in a text -- is in fact not a trivial skill, and very few people can manage it on their own. So, don't get too discouraged (or bored) because you don't seem to be doing interesting things just yet. After the basic concepts have sunk in somewhat, it will all come to you when we sit down in LING 1330 to write some linguistically interesting programs.AcknowledgmentsKudos to Ed and mybringback.com for producing such a wonderful video tutorial series. Additional thanks to Allen Downey of Think Python and Anne Dawson. Also, many thanks to Elliot Halpern and Christopher Kovalcik, Pitt linguistics majors, who helped with video summaries and proofreading. |