DJANGO
https://www.youtube.com/watch?v=F5mRW0jo-U4
https://www.udemy.com/course/python-and-django-full-stack-web-developer-bootcamp/
https://www.udemy.com/course/rest-api-flask-and-python/
1. Data scrapping 🔴⚫️⚪️🔵🔺🔻🔹🔶
https://www.coursera.org/learn/python-network-data/home/welcome
Syllabus – What you will learn from this course
Week 1 2 hours to complete
Getting Started
In this section you will install Python and a text editor. In previous classes in the specialization this was an optional assignment, but in this class it is the first requirement to get started. From this point forward we will stop using the browser-based Python grading environment because the browser-based Python environment (Skulpt) is not capable of running the more complex programs we will be developing in this class.
Welcome to The Course45s
Welcome to Python – Guido van Rossum1m
Windows 10: Installing Python and Writing A Program8m
Windows: Taking Screen Shots2m
Macintosh: Using Python and Writing A Program4m
Macintosh: Taking Screen Shots4m
Week 2 2 hours to complete
Regular Expressions (Chapter 11)
Regular expressions are a very specialized language that allow us to succinctly search strings and extract data from strings. Regular expressions are a language unto themselves. It is not essential to know how to use regular expressions, but they can be quite useful and powerful. 4 videos (Total 44 min), 1 reading, 2 quizzes
4 videos
11.1 – Regular Expressions10m
11.2 – Extracting Data15m
>>> import re
>>> x = ‘my 2 favorrite numbers are 19 and 42’
>>> y = re.findall(‘[0-9]+’, x)
>>> print(y)
[‘2′, ’19’, ’42’]
>>> y = re.findall(‘[AEIOU]+’, x)
>>> print(y)
[]
>>> x= ‘From: Using the : charater’
>>> y = re.findall(‘^F.+:’, x)
>>> print(y)
[‘From: Using the :’]
>>> y = re.findall(‘^F.+?:’, x)
>>> print(y)
[‘From:’]
>>>
>>> import re
>>> x = ‘From stephen.marquard@uct.ac.za Sat Jan 5 09:14:16 2008’
>>> y = re.findall(‘\S+@\S+’, x)
>>> print(y)
[‘stephen.marquard@uct.ac.za’]
>>> data = x
>>> atpos = data.find(‘@’)
>>> print(atpos)
21
>>> sppos = data.find(‘ ‘,atpos)
>>> print(sppos)
31
>>> host = data [atpos+1 : sppos]
>>> print(host)
uct.ac.za
>>> line = x
>>> words = line.split()
>>> email = words[1]
>>> pieces = email.split(‘@’)
>>> print(pieces[1])
uct.ac.za
>>> lin = x
>>> y = re.findall(‘@([^ ]*)’, lin)
>>> print(y)
[‘uct.ac.za’]
>>> y = re.findall(‘^From.*@([^ ]*)’, lin)
>>> print(y)
[‘uct.ac.za’]
>>> x = ‘we just received $10.00 for cookies.’
>>> y = re.findall(‘\$[0-9.]+’, x)
>>> print(y)
[‘$10.00’]
>>> x = ‘we just received €10,00 for cookies.’
>>> y = re.findall(‘\€[0-9,]+’, x)
>>> print(y)
[‘€10,00’]
Bonus: Office Hours – Den Haag2m
Bonus Interview: Bjarne Stroustrup – C++15m
1 reading
Python Regular Expression Quick Guide10m
1 practice exercise
Regular Expressions20m
Week 3 3 hours to complete
Networks and Sockets (Chapter 12)
In this section we learn about the protocols that web browsers use to retrieve documents and web applications use to interact with Application Program Interfaces (APIs). 8 videos (Total 68 min), 1 reading, 2 quizzes
8 videos
12.1 – Networked Technology7m
12.2 – Hypertext Transfer Protocol (HTTP)14m
Worked Example: Sockets (Chapter 12)6m
Using the Developer Console to Explore HTTP10m
Bonus: Leonard Kleinrock – The First Two Packets on the ARPANET13m
Bonus Video: Robert Cailliau – co-Inventor of the Web9m
Bonus: Office Hours – Atlanta GA (Buckhead)3m
Fun: Dr. Chuck @ CNN Reading the News4m
1 reading
If You Want to Learn More10m
Week 4 4 hours to complete
Programs that Surf the Web (Chapter 12)
In this section we learn to use Python to retrieve data from web sites and APIs over the Internet. 8 videos (Total 58 min), 1 reading, 3 quizzes
8 videos
12.3 – Unicode Characters and Strings17m
12.4 – Retrieving Web Pages6m
Worked Example: Using Urllib (Chapter 12)3m
12.5 – Parsing Web Pages9m
Worked Example: BeautifulSoup (Chapter 12)9m
Bonus: Office Hours – Montreal4m
Bonus Interview: Tim Berners-Lee – Inventing the Web1m
Fun: I Got My Mojo Working – Geneva, Switzerland5m
Week 5 2 hours to complete
Web Services and XML (Chapter 13)
In this section, we learn how to retrieve and parse XML (eXtensible Markup Language) data. 8 videos (Total 62 min), 2 quizzes
Week 6 4 hours to complete
JSON and the REST Architecture (Chapter 13)
In this module, we work with Application Program Interfaces / Web Services using the JavaScript Object Notation (JSON) data format. 12 videos (Total 95 min), 2 readings, 3 quizzes
12 videos
13.5 – JavaScript Object Notation (JSON)9m
Worked Example: JSON (Chapter 13)5m
Interview: Douglas Crockford – Discovering JSON7m
13.6 – Service Oriented Approach2m
Video: Service Oriented Architectures5m
13.7 – Using Application Programming Interfaces8m
Worked Example: GeoJSON API (Chapter 13)7m
13.8 – Securing API Requests11m
Worked Example: Twitter API (Chapter 13)19m
Bonus: Office Hours – Melbourne, AU1m
Bonus: Office Hours – Santa Monica, CA7m
Bonus: Class Reunion at Bletchley Park9m
2.Applied Text Mining
https://www.coursera.org/learn/python-text-mining/home/welcome
3. PANDAS with coursera AND
https://www.udemy.com/course/machinelearning/learn/lecture/6087180?start=0#overview
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HASKELL
OOP IN PYTHON
https://www.youtube.com/watch?v=qiSCMNBIP2g
https://www.youtube.com/watch?v=ZDa-Z5JzLYM