CSSE 290: Cognitive Computing
Rose-Hulman Institute of Technology
Computer Science Department
Spring 2015/16

Course Description

In this course, we get a chance to train and explore IBM's Watson. Watson is a question-answering system that advanced the state of the art of AI by several orders of magnitude and is a harbinger of things to come. It is an example of fine engineering and is considered a modern engineering marvel. IBM is arguing that this sort of technology will lead to cognitive assistants; software that intelligently processes high-level information. In this course, we will:
  1. develop an application that at its heart uses IBM's Watson question-answering technology,
  2. train an instance of Watson. This requires developing about 1200 question-answer pairs for a domain of our choosing,
  3. study several ways with which entrepreneurs determine potentially successful products,
  4. research and propose a potentially successful application,
  5. use a recruitment approach to select a domain for training,
  6. use the innovation canvas to justify an application,
  7. learn about the process of taking a product to market,
  8. learn about the underlying technology and techniques of IBM Watson, and
  9. assess the current state of the art in Cognitive Systems and develop an intuition about its future direction.

Prerequisites

CSSE 230 and junior standing

Outcomes

Students who successfully complete this course should be able to:
  1. Develop applications for Watson.
  2. Develop potentially successful applications in Cognitive Computing.
  3. Explain the architecture of Watson.
  4. Evaluate future directions of Cognitive Computing.
  5. Use the Innovation Canvas to justify potentially successful products.
  6. Explain various ways in which to develop a product idea.
  7. Explain the process of taking a product to market.

Instructor

Schedule

Assessment

The following assignments will be given in this course and used to assess the course objectives as indicated in the assessment matrix.
  1. Slides, presentation and write-up justifying a project idea.
  2. Slides, presentation and write-up of a project proposal (several rounds, recruitment).
  3. Presentation of ways in which innovators/artists develop an idea.
  4. Training data and training of our instance of Watson.
  5. Project software.
  6. Documentation of project through a technical paper, a slide presentation and a videotaped demo.
  7. Reviews of papers, videos and presentations about Watson and Cognitive Computing.
  8. Take-home final justifying the future of Cognitive Systems.
  9. Review of class presentations about the process of taking a product to market.
  10. Participation in class discussions.

Grading

ComponentWeight
Project proposal process20%
Project and documentation50%
Presentations, Reviews20%
Take-home final5%
Class participation5%

Citizenship

The success of this course depends on your active participation in class. Please come to class prepared and do things that contribute to your learning and that of others.

Academic Integrity

See the departmental statement on academic honesty.