Learn Python Programming - Easy as Pie : From 0 to 1

About Course

•  

  • Introductory Python: Functional language constructs; Python syntax; Lists, dictionaries, functions and function objects; Lambda functions; iterators, exceptions and file-handling
  • Database operations: Just as much database knowledge as you need to do data manipulation in Python
  • Auto-generating spreadsheets: Kill the drudgery of reporting tasks with xlsxwriter; automated reports that combine database operations with spreadsheet auto-generation
  • Text processing and NLP: Python’s powerful tools for text processing - nltk and others.
  • Website scraping using Beautiful Soup: Scrapers for the New York Times and Washington Post
  • Machine Learning : Use sk-learn to apply machine learning techniques like KMeans clustering

  • Hundreds of lines of code with hundreds of lines of comments

  • Drill #1: Download a zip file from the National Stock Exchange of India; unzip and process to find the 3 most actively traded securities for the day
  • Drill #2: Store stock-exchange time-series data for 3 years in a database. On-demand, generate a report with a time-series for a given stock ticker
  • Drill #3: Scrape a news article URL and auto-summarize into 3 sentences
  • Drill #4: Scrape newspapers and a blog and apply several machine learning techniques - classification and clustering to these

Curriculam

• Section 1: What is coding? - It's a lot like cooking!
  	Lecture 1	Introduction	02:51
  	Lecture 2	Coding is like Cooking	07:36
  	Lecture 3	Variables are like containers	11:01
  	Lecture 4	Anaconda and Pip	09:00
  	Quiz 1	Coding	3 questions
  Section 2: Don't Jump Through Hoops, Use Dictionaries, Lists and Loops
  	Lecture 5	A List is a list	09:17
  	Lecture 6	Fun with Lists!	08:44
  	Lecture 7	Dictionaries and If-Else	06:18
  	Lecture 8	Don't Jump Through Hoops, Use Loops	04:26
  	Lecture 9	Doing stuff with loops	05:29
  	Lecture 10	Everything in life is a list - Strings as lists	07:07
  	Quiz 2	Lists, Dictionaries and Loops	6 questions
  Section 3: Our First Serious Program
  	Lecture 11	Modules are cool for code-reuse	02:31
  	Lecture 12	Our first serious program : Downloading a webpage	17:48
  	Lecture 13	A few details - Conditionals	07:48
  	Lecture 14	A few details - Exception Handling in Python	07:48
  	Quiz 3	Modules,Conditionals and Exception Handling	3 questions
  Section 4: Doing Stuff with Files
  	Lecture 15	A File is like a barrel	11:21
  	Lecture 16	Autogenerating Spreadsheets with Python	09:15
  	Lecture 17	Autogenerating Spreadsheets - Download and Unzip	17:14
  	Lecture 18	Autogenerating Spreadsheets - Parsing CSV files	18:34
  	Lecture 19	Autogenerating Spreadsheets with XLSXwriter	05:25
  	Quiz 4	Files	5 questions
  Section 5: Functions are like Foodprocessors
  	Lecture 20	Functions are like Foodprocessors	10:58
  	Lecture 21	Argument Passing in Functions	16:30
  	Lecture 22	Writing your first function	12:54
  	Lecture 23	Recursion	16:56
  	Lecture 24	Recursion in Action	05:41
  	Quiz 5	Functions	6 questions
  Section 6: Databases - Data in rows and columns
  	Lecture 25	How would you implement a Bank ATM?	17:39
  	Lecture 26	Things you can do with Databases - I	20:06
  	Lecture 27	Things you can do with Databases - II	08:12
  	Lecture 28	Interfacing with Databases from Python	06:46
  	Lecture 29	SQLite works right out of the box	06:27
  	Lecture 30	Manually downloading the zip files required	Article
  	Lecture 31	Build a database of Stock Movements - I	15:01
  	Lecture 32	Build a database of Stock Movements - II	13:48
  	Lecture 33	Build a database of Stock Movements - III	13:22
  	Quiz 6	Databases	5 questions
  Section 7: An Object Oriented State of Mind
  	Lecture 34	Objects are like puppies!	03:45
  	Lecture 35	A class is a type of variable	17:31
  	Lecture 36	An Interface drives behaviour	13:40
  	Quiz 7	OOPS	4 questions
  Section 8: Natural Language Processing and Python
  	Lecture 37	Natural Language Processing with NLTK	07:26
  	Lecture 38	Natural Language Processing with NLTK - See it in action	14:14
  	Lecture 39	Web Scraping with BeautifulSoup	18:09
  	Lecture 40	A Serious NLP Application : Text Auto Summarization using Python	12:00
  	Lecture 41	Autosummarize News Articles - I	18:33
  	Lecture 42	Autosummarize News Articles - II	11:28
  	Lecture 43	Autosummarize News Articles - III	10:23
  	Quiz 8	NLP	2 questions
  Section 9: Machine Learning and Python
  	Lecture 44	Machine Learning - Jump on the Bandwagon	16:31
  	Lecture 45	Plunging In - Machine Learning Approaches to Spam Detection	17:30
  	Lecture 46	Spam Detection with Machine Learning Continued	19:04
  	Lecture 47	News Article Classification using K-Nearest Neighbors	20:00
  	Lecture 48	News Article Classification using Naive Bayes	19:47
  	Lecture 49	Code Along - Scraping News Websites	18:51
  	Lecture 50	Code Along - Feature Extraction from News articles	15:45
  	Lecture 51	Code Along - Classification with K-Nearest Neighbours	04:15
  	Lecture 52	Code Along - Classification with Naive Bayes	08:08
  	Lecture 53	Document Distance using TF-IDF	11:22
  	Lecture 54	News Article Clustering with K-Means and TF-IDF	15:07
  	Lecture 55	Code Along - Clustering with K-Means	08:32
  	Quiz 9	Machine Learning	7 questions

What you will get from this course?

• • Pick up programming even if you have NO programming experience at all
  • Write Python programs of moderate complexity
  • Perform complicated text processing - splitting articles into sentences and words and doing things with them
  • Work with files, including creating Excel spreadsheets and working with zip files
  • Apply simple machine learning and natural language processing concepts such as classification, clustering and summarization
  • Understand Object-Oriented Programming in a Python context

Who should buy this course?

• • Folks with zero programming experience looking to learn a new skill
  • Machine Learning and Language Processing folks looking to apply concepts in a full-fledged programming language
  • Computer Science students or software engineers with no experience in Java, but experience in Python, C++ or even C#. You might need to skip over some bits, but in general the class will still have new learning to offer you.