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