If you are already good with OOPS then take a look at this and see if you can make sense of it..
https://stephensugden.com/crash_into_python/
Else go with these
Choose any one- http://learnpythonthehardway.org/book/
http://greenteapress.com/wp/think-python/ (recommended)
http://www.diveintopython.net/
http://www.python-course.eu/course.php
Python Intermediate taoofmac.com/media/TgSX-8pK9VpD3RjVOWv1pxt-co4=/d…
#Examples and Projects With Python - Hands on Python Tuts
https://automatetheboringstuff.com/
(The Part 2 section in this site is awesome)
#2(There are quite a few tutorials, browse through and re-create few projects by following them)
https://www.codementor.io/python/tutorial
#3 Awesome Python Recipes (1000+ recipes)
code.activestate.com/recipes/langs/python
#4 More recipes I just love this site!
Moving to advanced applications of Python Text Analytics & Machine Learning http://www.nltk.org/
Sentiments Analysis is one of the hot research areas for undergrads these days...you can follow this tutorial to begin
streamhacker.com/2010/05/10/text-classification-s…
pythonprogramming.net/tokenizing-words-sentences-…
Data Analysis Fundamentals with Python http://www.pythonlearn.com/book.php
And as for video tutorials
www.udacity.com and www.coursera.com has pretty rich collection of Courses on Machine Learning, AI and Data Analytics using Python. Special mention for Udacity's ML course, its pretty easy to follo
There are so many excellent resources out there, and a simple search could direct you to the right one. So apart from doing that, let me share you the learning experiences that I have come across; which might help you in finding your right resource; and a way to master it.
In one of my previous stints, involving computational biology, I took up the role of teaching programming to a group of Ph.D. scholars in my lab. While everyone of them was enthusiastic at the beginning, the interest slowly started to drift away. The reason behind the loss of interest, was the resource which I chose to use for the task — an excellent programming book, if I might add — How to Think Like a Computer Scientist: Think Python
It didn't take much, to figure out that they didn't connect with that book, as it, apart from being a phenomenal learning resource, had nothing contextual for a biologist. Soon after, we shifted to the book: Python for Biologists... and well, it turned out to be really awesome.
The lesson I have learnt from this whole endeavour, which I probably already knew but wouldn't have been able to articulate better had I not gone through the above experience, is this:
You learn in an accelerated fashion, when the learning resources use the same context in which you want to achieve results.
Let me give another example, I am excited about game development; so I had a ball of a time, going through the Coursera course, Interactive Programming with Python, where you built small games after every lesson.
So, what's your context? Why do you want to learn Python? Is it because you want to build websites, work with financial models, wrangle biological data, or build games?
The best approach to learn, and master any programming language, in my opinion, and experience; is to go through consistent checks of what you've learned so far, through building tiny, trivial projects; and to seek feedback on your result from the experienced.
In Interactive Programming with Python, right after you're given an intro on the basic things like variables, and conditionals; you're off to building a number guessing game.
Another course which I greatly enjoyed, and which follows the above approach, is Udacity's Intro to Computer Science, which not only introduces you to the fundamentals of computer science, in an "Oh, so awesome!" way; but ensures you are building little parts of a basic search engine, after every lesson.
Check this one .. www.sololearn.com ... it is very good
They have a very powerfull mobile app
Ritwik Sahoo
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