Curriculum
1 Section
55 Lessons
52 Weeks
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Course Curriculum
What is Coding? Its a lot like Cooking!
55
2.1
Cooking is like coding
7 Minutes
2.2
Anaconda And Pip
9 Minutes
2.3
A list is a list!
9 Minutes
2.4
Fun with Lists
8 Minutes
2.5
Dictionaries and if else
6 Minutes
2.6
Don’t Jump throligh Hoops, use loops
4 Minutes
2.7
Doing stuff with loops
5 Minutes
2.8
Everything in life is a list – Strings as lists
7 Minutes
2.9
Modules are cool for code-reuse
2 Minutes
2.10
Our first serious program : Downloading a webpage
17 Minutes
2.11
A few details – Conditionals
7 Minutes
2.12
A few details – Exception Handling in Python
7 Minutes
2.13
A File is like a barrel
11 Minutes
2.14
Autogenerating Spreadsheets with Python
9 Minutes
2.15
Autogenerating Spreadsheets – Download and Unzip
17 Minutes
2.16
Autogenerating Spreadsheets – Parsing CSV files
18 Minutes
2.17
Autogenerating Spreadsheets with XLSXwriter
5 Minutes
2.18
Functions are like Foodprocessors
10 Minutes
2.19
Argument Passing in Functions
12 Minutes
2.20
Writing your first function
12 Minutes
2.21
Recursion
16 Minutes
2.22
Recursion in Action
5 Minutes
2.23
How would you implement a Bank ATM?
5 Minutes
2.24
Things you can do with Databases – I
20 Minutes
2.25
Things you can do with Databases – II
20 Minutes
2.26
Interfacing with Databases from Python
8 Minutes
2.27
SQLite works right out of the box
6 Minutes
2.28
Build a database of Stock Movements – I
6 Minutes
2.29
Build a database of Stock Movements – II
30 Minutes
2.30
Build a database of Stock Movements – III
15 Minutes
2.31
Objects are like puppies!
13 Minutes
2.32
A class is a type of variable
13 Minutes
2.33
An Interface drives behaviour
3 Minutes
2.34
Classes_Intro
17 Minutes
2.35
Interfaces
13 Minutes
2.36
Natural Language Processing with NLTK
7 Minutes
2.37
Natural Language Processing with NLTK – See it in action
14 Minutes
2.38
Web Scraping with Beautiful Soup
18 Minutes
2.39
A Serious NLP Application : Text Auto Summarization using Python
11 Minutes
2.40
Autosummarize News Articles – I
18 Minutes
2.41
Autosummarize News Articles – II
30 Minutes
2.42
Autosummarize News Articles – III
10 Minutes
2.43
Machine Learning – Jump on the Bandwagon
16 Minutes
2.44
Plunging In – Machine Learning Approaches to Spam Detection
17 Minutes
2.45
Spam Detection with Machine Learning Continued
19 Minutes
2.46
News Article Classification using K-Nearest Neighbors
19 Minutes
2.47
News Article Classification using Naive Bayes
19 Minutes
2.48
Code Along – Scraping News Websites
18 Minutes
2.49
Code Along – Feature Extraction from News articles
15 Minutes
2.50
Code Along – Classification with K-Nearest Neighbours
4 Minutes
2.51
Code Along – Classification with Naive Bayes
8 Minutes
2.52
Document Distance using TF-IDF
11 Minutes
2.53
News Article Clustering with K-Means and TF-IDF
30 Minutes
2.54
Code Along – Clustering with K-Means
30 Minutes
2.55
Variables are like Containers
11 Minutes
From 0 to 1: Learn Python Programming – Easy as Pie
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