Modules
Chapter 01: What is coding? – It’s a lot like cooking!
Lesson 01: Introduction
Lesson 02: Coding is like Cooking
Lesson 03: Anaconda and Pip
Lesson 04: Variables are like containers
Chapter 02: Don’t Jump Through Hoops, Use Dictionaries, Lists and Loops
Lesson 01: A List is a list
Lesson 02: Fun with Lists!
Lesson 03: Dictionaries and If-Else
Lesson 04: Don’t Jump Through Hoops, Use Loops
Lesson 05: Doing stuff with loops
Lesson 06: Everything in life is a list – Strings as lists
Chapter 03: Our First Serious Program
Lesson 01: Modules are cool for code-reuse
Lesson 02: Our first serious program : Downloading a webpage
Lesson 03: A few details – Conditionals
Lesson 04: A few details – Exception Handling in Python
Chapter 04: Doing Stuff with Files
Lesson 01: A File is like a barrel
Lesson 02: Auto Generating Spreadsheets with Python
Lesson 03: Auto Generating Spreadsheets – Download and Unzip
Lesson 04: Auto Generating Spreadsheets – Parsing CSV files
Lesson 05: Auto Generating Spreadsheets with XLSXwriter
Chapter 05: Functions are like Food Processors
Lesson 01: Functions are like Food processors
Lesson 02: Argument Passing in Functions
Lesson 03: Writing your first function
Lesson 04: Recursion
Lesson 05: Recursion in Action
Chapter 06: Databases – Data in rows and columns
Lesson 01: How would you implement a Bank ATM?
Lesson 02: Things you can do with Databases – I
Lesson 03: Things you can do with Databases – II
Lesson 04: Interfacing with Databases from Python
Lesson 05: SQLite works right out of the box
Lesson 06: Manually downloading the zip files required
Lesson 07: Build a database of Stock Movements – I
Lesson 08: Build a database of Stock Movements – II
Lesson 09: Build a database of Stock Movements – III
Chapter 07: An Object Oriented State of Mind
Lesson 01: Objects are like puppies!
Lesson 02: A class is a type of variable
Lesson 03: An Interface drives behaviour
Chapter 08: Natural Language Processing and Python
Lesson 01: Natural Language Processing with NLTK
Lesson 02: Natural Language Processing with NLTK – See it in action
Lesson 03: Web Scraping with BeautifulSoup
Lesson 04: A Serious NLP Application : Text Auto Summarization using Python
Lesson 05: Auto Summarize News Articles – I
Lesson 06: Auto Summarize News Articles – II
Lesson 07: Auto Summarize News Articles – III
Chapter 09: Machine Learning and Python
Lesson 01: Machine Learning – Jump on the Bandwagon
Lesson 02: Plunging In – Machine Learning Approaches to Spam Detection
Lesson 03: Spam Detection with Machine Learning Continued
Lesson 04: News Article Classification using K-Nearest Neighbors
Lesson 05: News Article Classification using Naive Bayes
Lesson 06: Code Along – Scraping News Websites
Lesson 07: Code Along – Feature Extraction from News articles
Lesson 08: Code Along – Classification with K-Nearest Neighbours
Lesson 09: Code Along – Classification with Naive Bayes
Lesson 10: Document Distance using TF-IDF
Lesson 11: News Article Clustering with K-Means and TF-IDF
Lesson 12: Code Along – Clustering with K-Means
System Requirements
Minimum specifications for the computer are:
Windows:
Microsoft Windows XP, or later
Modern and up to date Browser (Internet Explorer 8 or later, Firefox, Chrome, Safari)
MAC/iOS:
OSX/iOS 6 or later
Modern and up to date Browser (Firefox, Chrome, Safari)
All systems:
Internet bandwidth of 1Mb or faster
Flash player or a browser with HTML5 video capabilities (We recommend Google Chrome)
Unlimited access for 12 months
Access anywhere, any time
