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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