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| CSCI 381: Language, Intelligence, and Computation |
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Catalog Description:
This course presents a practically based treatment of artificial intelligence, and a general introduction of technical issues associataed with the development of intelligent systems. The course addresses issues of knowledge representation and natural language processing in particular, from a computational perspective. Students write programs to perform simple analyses of natural language and logical reasoning. Students also explore the limits of computation, using practical and theoretical approaches. 2.0 hours lecture, 2.0 hours activity. This is an approved General Education course. Formerly CSCI 123.
Course Objectives:
The primary objective of this course is to introduce students to the basic principles and programming techniques employed when designing and implementing applications of artificial intelligence. Emphasis will be placed on the teaching of these fundamentals at a simplistic level, not on providing a mastery of specific software tools, languages, or programming environments. Assigned projects promote a 'hands-on' approach for understanding, as well as a challenging avenue for exploration and creativity.
Specifically:
- Gain a historical perspective of AI and its foundations. (B)
- Receive an introduction to the basic principles of AI toward problem solving, perception, knowledge representation, language processing, and learning. (B)
- Experience applications of AI within expert systems, artificial neural networks and other machine learning models. (B)
- Experience basic programming in Lisp and/or high-level AI logic tools. (B)
Discuss the potential, limitations, and implications of intelligent systems.
B=Basic I=Intermediate A=Advanced
Course Outcomes:
Upon successful completion of this course, students should possess the following:
- An appreciation for the history of AI
- Basic problem-solving strategies for approaching AI solutions
- Beginner-level skill set for programming in Lisp
- Beginner-level skill set for using a subset of AI applications and modeling tools
Class/Laboratory Schedule:
Two hours lecture/discussion plus two hours lab activity, weekly.
Accreditation Category Content: |
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| Topic |
Percentage |
Hours |
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| Algorithms |
25% |
12 |
| Data Structures |
10% |
5 |
| Software Design |
25% |
12 |
| Concepts of Programming |
10% |
5 |
| Computer Organization and Architecture |
0% |
0 |
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Relationship of Course to Program Objectives:
This course supports the achievement of the following program objectives:
- All students will be able to analyze and solve computing problems, or problems in related areas, and to continually upgrade their knowledge and skills. (I)
- All students will be effective oral and written communicators and be able to function effectively as members of multi-disciplinary teams. (I)
- All students will have an appreciation for the individual, society, and human heritage and they will be aware of the impact of their work on society and the environment. (I)
- Those graduates who pursue careers as computing professionals will have the skills to use and design new and innovative systems that meet society's needs. (I)
- Those graduates who pursue advanced degrees will have the skills to succeed in graduate programs in computing and related fields. (I)
I=Introduced P=Practiced R=Reinforced |
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Management
California State University, Chico |
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Science, & Construction Management
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Chico, CA 95929-0003
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