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Introduction to Python
Introduction

1 - Installing Python

2 - Numbers

3 - Strings

4 - Slicing up Strings

5 - Lists

6 - Installing PyCharm

Conditional Statements

7 - if elif else

Iterations

8 - for

9 - Range and While

10 - Comments and Break

11 - Continue

Functions

12 - Functions

13 - Return Values

14 - Default Values for Arguments

15 - Variable Scope

16 - Keyword Arguments

17 - Flexible Number of Arguments

18 - Unpacking Arguments

19 - My trip to Walmart and Sets

20 - Dictionary

21 - Modules

Playing with Requests and Files

22 - Download an Image from the Web

23 - How to Read and Write Files

24 - Downloading Files from the Web

Exceptions

28 - Exceptions

Object Oriented Programs

29 - Classes and Objects

30 - init

31 - Class vs Instance Variables

32 - Inheritance

33 - Multiple Inheritance

34 - threading

Playing around with Python

35 - Unpack List or Tuples

36 - Zip (and yeast infection story)

37 - Lamdba

38 - Min, Max, and Sorting Dictionaries

39 - Pillow

40 - Cropping Images

41 - Combine Images Together

42 - Getting Individual Channels

43 - Awesome Merge Effect

44 - Basic Transformations

45 - Modes and Filters

46 - struct

47 - map

48 - Bitwise Operators

49 - Finding Largest or Smallest Items

50 - Dictionary Calculations

51 - Finding Most Frequent Items

52 - Dictionary Multiple Key Sort

53 - Sorting Custom Objects

Add Ons:

54 - Database Connectivity and Querying for MySQL

55 - Quick look into Regular Expressions

56 - Playing around with REST API

Writing a Web Crawler

Natural Language Processing and NLTK
Introduction to NLP (examples in Python of course)

Simple Text Manipulation

Searching Text

Counting Words

Splitting Texts into Words

Lexical dispersion

Processing complex structures

Representing text in Lists

Indexing Lists

Collocations

Bigrams

Frequency Distributions

Conditionals with Words

Comparing Words (startswith, endswith, islower, isalpha, etc...)

Natural Language Understanding

Word Sense Disambiguation

Pronoun Resolution

Machine translations (statistical, rule based, literal, etc...)

Exercises

NLP in Python in examples

Accessing Text Corpora and Lexical Resources

Common sources for corpora

Conditional Frequency Distributions

Counting Words by Genre

Creating own corpus

Pronouncing Dictionary

Shoebox and Toolbox Lexicons

Senses and Synonyms

Hierarchies

Lexical Relations: Meronyms, Holonyms

Semantic Similarity

Processing Raw Text

Priting

struncating

extracting parts of string

accessing individual charaters

searching, replacing, spliting, joining, indexing, etc...

using regular expressions

detecting word patterns

stemming

tokenization

normalization of text

Word Segmentation (especially in Chinese)

Categorizing and Tagging Words

Tagged Corpora

Tagged Tokens

Part-of-Speech Tagset

Python Dictionaries

Words to Propertieis mapping

Automatic Tagging

Determining the Category of a Word (Morphological, Syntactic, Semantic)

Text Classification (Machine Learning)

Supervised Classification

Sentence Segmentation

Cross Validation

Decision Trees

Extracting Information from Text

Chunking

Chinking

Tags vs Trees

Analyzing Sentence Structure

Context Free Grammar

Parsers

Building Feature Based Grammars

Grammatical Features

Processing Feature Structures

Analyzing the Meaning of Sentences

Semantics and Logic

Propositional Logic

First-Order Logic

Discourse Semantics

Managing Linguistic Data

Data Formats (Lexicon vs Text)

Metadata