Sentiment Analysis

Sentiment Analysis

taught by Robert Munro and Nitin Indurkhya

 

This course is recognized by the Operations Research Society (INFORMS) as useful preparation for the Certified Analytics Professional (CAP) exam. Complete info below to test your CAP readiness with a practice exam from INFORMS.
 
 
 
 

Aim of Course:

This online course, “Sentiment Analysis,” is designed to give you an introduction to the algorithms, techniques and software used in sentiment analysis. Their use will be illustrated by reference to existing applications, particularly product reviews and opinion mining. The course will try to make clear both the capabilities and the limitations of these applications. For real-world applications, sentiment analysis draws heavily on work in computational linguistics and text-mining. At the completion of the course, a student will have a good idea of the field of sentiment analysis, the current state-of-the-art and the issues and problems that are likely to be the focus of future systems.

 

This course may be taken individually (one-off) or as part of a certificate program.

Course Program:

WEEK 1: Introduction and Subjectivity Analysis

  • Text Categorization concepts
  • Computational Linguistics concepts
  • Subjectivity Analysis

WEEK 2: Sentiment Extraction

  • Topic Extraction
  • Product Reviews
  • Sentiment analysis of Comparative Sentences
  • Applications

WEEK 3: Opinion Retrieval and Spam

  • Searching for Opinions
  • Opinion Summarization
  • Opinion Spam
  • Applications

HOMEWORK:

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

In addition to assigned readings, this course also has supplemental readings available online.

Sentiment Analysis

Who Should Take This Course:

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

Level:

ADVANCED / INTERMEDIATE - see prerequisites

Prerequisite:
This course covers a rapidly evolving field and the material is taken from academic publications, so mathematical maturity and the ability to read conference/journal papers are needed.  If you have some familiarity and comfort with the prerequisites, you may be able to make do with just one of the two listed above.

Organization of the Course:

This course takes place online at the Institute for 3 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.

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.

Time Requirement:
About 15 hours per week, at times of  your choosing.

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. No credit - You may be interested only in learning the material presented, and not be concerned with grades or a record of completion.
  2. Certificate - 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. CEUs and/or proof of completion - 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,  CEU's and a record of course completion will be issued by The Institute, upon request.
  4. Other options - Statistics.com Specializations, INFORMS CAP recognition, and academic (college) credit are available for some Statistics.com courses
Specialization:
Specializations are an easy way for you to demonstrate mastery of a specific skill in statistics and analytics. This couse is part of the Text Mining and Analytics Specialization which gives a deep dive into text mining, natural language processing and sentiment analysis. Requires Python and some familiarity with Bayesian statistics.  Take any three of the four Statistics.com courses listed to the right (related courses).  For savings, use the promo code "text-specialization" and register for all three courses at once for  $1197 ($399 per course, not combinable with other tuition savings).  If you register for all four, you'll still receive the discounted rate.


Sentiment Analysis has been evaluated by the American Council on Education (ACE) and is recommended for the upper-division baccalaureate degree category, 2 semester hours in computer sciences or text data mining. Note: The decision to accept specific credit recommendations is up to each institution. More info here.
This course is also recognized by the Institute for Operations Research and the Management Sciences (INFORMS) as helpful preparation for the Certified Analytics Professional (CAP®) exam, and can help CAP® analysts accrue Professional Development Units to maintain their certification .

Course Text:

All materials will be made available in the course.

Software:

None

Instructor(s):

Dates:

August 18, 2017 to September 08, 2017 August 17, 2018 to September 07, 2018

Sentiment Analysis

Instructor(s):

Dates:
August 18, 2017 to September 08, 2017 August 17, 2018 to September 07, 2018

Course Fee: $469

Do you meet course prerequisites? What about book & software? (Click here to learn more)

Group rates: Click here to get information on group rates. 

First time student or academic? Click here for an introductory offer on select courses. Academic affiliation?  You may be eligible for a discount at checkout.

Take 3 or 4 text analytics courses, save $100 per course (code text2016).

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