Natural Language Processing

taught by Nitin Indurkhya

Brief Description:

This course is designed to give you an introduction to the algorithms, techniques and software used in natural language processing (NLP).

Instructor(s):
Level: Intermediate

Who Should Take This Course:

Analysts, researchers and managers who deal with, or might need to deal with, NLP systems at a variety of levels - needs assessment, design, deployment and operation.

Dates:
July 20, 2012 to August 17, 2012July 19, 2013 to August 16, 2013
language Click here to be reminded of future sessions of this course.

Registration:
Please read the syllabus tab, noting the prerequisites, text and software requirements.

Register Online -$499
Register Online -$399 (you must be affiliated with a college, university or high school)

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Natural Language Processing

taught by Nitin Indurkhya

Aim of Course:

This course is designed to give you an introduction to the algorithms, techniques and software used in natural language processing (NLP). Their use will be illustrated by reference to existing applications, particularly speech understanding, information retrieval, machine translation and information extraction. The course will try to make clear both the capabilities and the limitations of these applications.

For real-world applications, NLP draws heavily on work in computational linguistics and artificial intelligence. The course textbook will provide the necessary background in linguistics and computer science for those students who need it. In this course only a portion of the textbook will be covered, however anyone going on to do further studies in NLP will find the textbook a very useful reference.

At the completion of the course, a student should be able to read the description of an NLP application and have an idea of how it is done, what the likely weaknesses are, and often which claims are probably exaggerated. The course also prepares students to do further work in NLP by giving them a good grasp of the basic concepts.

Prerequisite(s):
Students should be familiar with probability (e.g. the material covered in Statistics 1 and Statistics 2). Some familiarity with Bayesian statistics (such as that covered in Introduction to Bayesian Statistics) is also helpful, although the text does cover the required Bayesian fundamentals to a limited degree. Keep in mind that this course is an introductory/survey course with a broad brush approach, and, as such, does not get into computational intensity on a comprehensive basis.

 

Course Program:

SESSION 1: Introduction of NLP and Word-level Analysis

• Overview of NLP
• Text Preprocessing
• Corpus Creation
• Fundamental Statistical Techniques in NLP (review)
• Lexical Analysis

SESSION 2: Sentence-level Processing

• Part-of-Speech Tagging
• Context-Free Grammars (CFG)
• Parsing of sentences with CFG
• Statistical parsing methods

SESSION 3: Semantics

• Representation of Meaning
• Semantic Analysis
• Word Sense Disambiguation

SESSION 4: Applications of NLP

• Information Retrieval
• Information Extraction
• Speech Recognition Systems
• Natural Language Generation

HOMEWORK:

Homework in this course consists of short answer questions to test concepts.

Organization of the Course:

This course takes place over the internet at the Institute for 4 weeks. During each course week, you participate at times of your own choosing - there are no set times when you must be online. Course participants will be given access to a private discussion board. In class discussions led by the instructor, you can post questions, seek clarification, and interact with your fellow students and the instructor.

The course typically requires 15 hours per week. At the beginning of each week, you receive the relevant material, in addition to answers to exercises from the previous session. During the week, you are expected to go over the course materials, work through exercises, and submit answers. Discussion among participants is encouraged. The instructor will provide answers and comments, and at the end of the week, you will receive individual feedback on your homework answers.

Credit:
Students come to the Institute for a variety of reasons. As you begin the course, you will be asked to specify your category:

1. You may be interested only in learning the material presented, and not be concerned with grades or a record of completion.
2. You may be enrolled in PASS (Programs in Analytics and Statistical Studies) that requires demonstration of proficiency in the subject, in which case your work will be assessed for a grade.
3. You may require a "Record of Course Completion," along with professional development credit in the form of Continuing Education Units (CEU's).  For those successfully completing the course, 5.0 CEU's and a record of course completion will be issued by The Institute, upon request.

Course Text:

The course text is Handbook of Natural Language Processing (2nd edition), by Nitin Indurkhya and Fred Damerau, which you can order from CRC Press, or by using this form. CRC Press typically gives students a generous discount when students order the text using the above form (not by ordering the text online).

PLEASE ORDER YOUR COPY IN TIME FOR THE COURSE STARTING DATE.

Software:

None.

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Natural Language Processing

taught by Nitin Indurkhya

Instructor(s):
Dates:
July 20, 2012 to August 17, 2012July 19, 2013 to August 16, 2013
Course Fee: $499
Academic Rate: $399

Before registering, please read the syllabus tab, noting the prerequisites, text and software requirements. When you click the register button, you will be taken to our secure transaction page.

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