NLP Training Courses

NLP Training

Natural Language Processing, Natural Language Processing courses

NLP Course Outlines

Code Name Duration Overview
python_nltk Natural Language Processing with Python 28 hours This course introduces linguists or programmers to NLP in Python. During this course we will mostly use nltk.org (Natural Language Tool Kit), but also we will use other libraries relevant and useful for NLP. At the moment we can conduct this course in Python 2.x or Python 3.x. Examples are in English or Mandarin (普通话). Other languages can be also made available if agreed before booking.Overview of Python packages related to NLP   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
nlp Natural Language Processing 21 hours This course has been designed for people interested in extracting meaning from written English text, though the knowledge can be applied to other human languages as well. The course will cover how to make use of text written by humans, such as  blog posts, tweets, etc... For example, an analyst can set up an algorithm which will reach a conclusion automatically based on extensive data source. Short Introduction to NLP methods word and sentence tokenization text classification sentiment analysis spelling correction information extraction parsing meaning extraction question answering Overview of NLP theory probability statistics machine learning n-gram language modeling naive bayes maxent classifiers sequence models (Hidden Markov Models) probabilistic dependency constituent parsing vector-space models of meaning

Upcoming Courses

CourseCourse DateCourse Price [Remote / Classroom]
Natural Language Processing - NB, Saint JohnMon, Dec 19 2016, 9:30 am$5050 / $8800
Natural Language Processing - NL, St. John's WestMon, Dec 19 2016, 9:30 am$5050 / $8800
Natural Language Processing - QC, Montreal - University StreetMon, Dec 19 2016, 9:30 am$5050 / $8800
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Course Discounts

Course Venue Course Date Course Price [Remote / Classroom]
Web Application Performance Testing with JMeter Remote Course Thu, Dec 15 2016, 9:30 am $1822 / N/A
WebServices with SOAP and WSDL Basics Remote Course Tue, Dec 20 2016, 9:30 am $3406 / N/A

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