• Computer Science

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    Ken Takata
    Program Director

    Art Guetter
    Program Director

  • Student working on a computer and relaxing

    Computer Science Courses at Hamline

    CSCI 1250 - Introduction to Computer Science

    Goals: To enable students to write moderate-sized programs for a variety of applications.

    Content: An introduction to computer science is designed for those students who would like to learn a modern programming language. The emphasis of this course is to introduce students to the fundamentals of programming and not just to a particular language.

    This course is taught using C++.

    Prerequisite: High school algebra.

    Credits: 4 courses

    CSCI 1500 - Introduction to Databases

    Goals: To understand the basics of designing, implementing, and using a database management system; to understand the difference among the three basic types of database systems: relational, hierarchical and network; to learn to use a commercially available database management system. In past years, this course has been taught using Microsoft Access.

    Content: Theoretical foundations of databases, query languages such as SQL, hands-on experience implementing a relational database.

    Taught: Alternate years.

    Credits: 4 credits

    CSCI 3150 - Data Structures

    Goals: The student will start from a basic knowledge of programming acquired in CSCI 1250 and further that knowledge by a study of recursion, pointers, and common programming structures needed for implementation of larger and more complex programs.

    Content: Linked lists, stacks, queues, sets, trees, graphs.

    Prerequisite: CSCI 1250.

    Credits: 4 credits 

    CSCI 3500 - Survey of Computational Science

    Goals: An introduction to quantitative modeling in the context of the disciplines that support the computational science minor.

    Content: Topics are chosen to prepare students to use computational methods. For example: mathematical modeling, optimization (discrete and dynamic), numerical methods, data mining, statistics (error analysis and stochastic modeling).

    Taught: Annually.

    Prerequisites: MATH 1180 and CSCI 1250.

    Credits: 4 credits

    CSCI 5850 - Numerical Analysis

    See MATH 5850.


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