Natural Language Processing

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 a Program of Advanced Statistical Studies, 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. Nitin Indurkhya is co-author of Text Mining, and Professor at the School of Computer Science and Engineering, University of New South Wales, Sydney, Australia. He is also the founder and president of Data-Miner Pty Ltd, an Australian company engaged in data-mining consulting and education. He has published extensively on data mining and has considerable experience with industrial data-mining applications in many countries such as Australia, Japan and the United States.

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 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 Program in Advanced Statistical Studies 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:

Aug. 20 - Sep. 17, 2010
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 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 (e.g. the material covered in Introduction to Statistics for Beginners, and the succeeding two courses at statistics.com). 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 Text:

The textbook for this course is Speech and Language Processing (2nd edition), by Daniel Jurafsky and James H. Martin, Prentice Hall, which can be ordered directly from the publisher here. Addison Wesley/Pearson offers a 15% discount on this book (and all other statistics titles): enter the code STATSMPS in the Promotion Code field when prompted during checkout and click the Apply Discount button. The 15% off discount will work for customers coming from anywhere in the world, except Canada. The free shipping only applies to orders shipping within the US.

Special note for Canadian customers: If you are located in Canada, you will need to make your order on myPearsonStore.ca site, which don't have the ability to offer discount codes. Try calling your regional Pearson representative. The US website will not let you choose "Canada" as a ship-to country. PLEASE ORDER YOUR COPY IN TIME FOR THE COURSE STARTING DATE.

Software:

None.

Registration:

Register Online - $469
Register Online (academic) - $369 (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.

Consider registering for this course together with two other Data Mining courses as part of our special 3 course package registration for tuition savings.

Note: Courses may fill up at any time and registrations are processed in the order in which they are received. When a course is marked "full" above your registration will be applied to the next available course date.

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