Natural Language Processing

Dr. Fred Damerau and Dr. 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.

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.

For those enrolled in Professional Advancement Programs, this is a required or elective course in the following Programs:

• Data Mining - elective

Course Program:

The course is structured as follows

The Instructor:

Dr. Fred Damerau, prior to his retirement, was a researcher at the Thomas J. Watson Research Center, Research Staff Linguistics group, where he worked on machine learning approaches to natural language processing. He is a co-author (With Weiss, Indurkhya and Zhang) of Text Mining. Nitin Indurkhya, co-author of Text Mining, and professor at the School of Computer Science and Engineering, University of New South Wales, Sydney, Australia, is also the founder and president of Data-Miner Pty Ltd, an Australian company engaged in data-mining consulting and education.

Organization of the Course:

The course takes place over the internet, at statistics.com. 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 is scheduled to take place over 4 weeks, and typically requires 10-15 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 and work through exercises. Discussion among participants is encouraged. The instructor will provide answers and comments.

Certificates and Grades:

You may be interested only in learning the material presented, and not be concerned with grades or certificates. Or you may be enrolled in a statistics.com Professional Advancement Program that requires demonstration of proficiency in the subject, in which case your work will be assessed for purposes of issuing a grade. Or you may require only a "Certificate of Course Completion," along with professional development credit in the form of Continuing Education Units (CEU's). As you begin the class, you will be asked to specify your category.

Credit:

This course offers continuing education units (CEU's). For those successfully completing the course (generally this means marks of 50% or better on the homework), 5.0 CEU's and a certificate will be issued by statistics.com, upon request.

Dates:

Sep. 26 - Oct. 24, 2008
Click here to be notified of future course offerings.

Participants gain access to the online materials on the first day of the course, and typically spend about 10-15 hours per week (at their convenience). You retain full access to course materials, including discussion board, for two weeks after the course closing date.

Level:

Intermediate

Prerequisite:

Students should be familiar with probability, and probabilistic modeling.

Course Text:

The textbook for this course is Speech and Language Processing (1st Edition), by Daniel Jurafsky and James H. Martin, Prentice Hall. Click here to purchase this book from the publisher, Prentice Hall. PLEASE ORDER YOUR COPY IN TIME FOR THE COURSE STARTING DATE.

Software:

None.

Registration:

Register Online - $449
Register Online (academic) - $349 (you must be affiliated with a college, university or high school)

Add $50 service fee if you require a prior invoice, or if you need to submit a purchase order or voucher, pay by wire transfer or EFT, or refund and reprocess a prior payment. Please use this printed registration form, for these and other special orders.

Note: Courses may fill up at any time and registrations are processed in the order in which they are received. Your registration will be confirmed for the first available course date, unless you specify otherwise.