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:
- develop an application that at its heart uses IBM's Watson
question-answering technology,
- train an instance of Watson. This requires developing about 1200
question-answer pairs for a domain of our choosing,
- study several ways with which entrepreneurs determine potentially
successful products,
- research and propose a potentially successful application,
- use a recruitment approach to select a domain for training,
- use the innovation canvas to justify an application,
- learn about the process of taking a product to market,
- learn about the underlying technology and techniques of IBM Watson, and
- 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:
- Develop applications for Watson.
- Develop potentially successful applications in Cognitive Computing.
- Explain the architecture of Watson.
- Evaluate future directions of Cognitive Computing.
- Use the Innovation Canvas to justify potentially successful products.
- Explain various ways in which to develop a product idea.
- Explain the process of taking a product to market.
Instructor
Assessment
The following assignments will be given in this course and used to assess the course objectives as indicated in the assessment matrix.
- Slides, presentation and write-up justifying a project idea.
- Slides, presentation and write-up of a project proposal (several rounds, recruitment).
- Presentation of ways in which innovators/artists develop an idea.
- Training data and training of our instance of Watson.
- Project software.
- Documentation of project through a technical paper, a slide presentation and a videotaped demo.
- Reviews of papers, videos and presentations about Watson and Cognitive Computing.
- Take-home final justifying the future of Cognitive Systems.
- Review of class presentations about the process of taking a product to market.
- Participation in class discussions.
Grading
Component | Weight
|
---|
Project proposal process | 20%
|
Project and documentation | 50%
|
Presentations, Reviews | 20%
|
Take-home final | 5%
|
Class participation | 5%
|
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.