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Topics in Mathematics

I.     Course Prefix/Number: MAT 290

       Course Name: Topics in Mathematics

       Credits: 1-4 (0-4 lecture; 0-4 lab)

II.    Prerequisite

Prerequisite may vary by topic.

III.   Course (Catalog) Description

Course covers variety of different topics during different semesters. Topics are selected from amongst current advances and faculty expertise. Typical course concentrations might be History of Mathematics or Introduction to MathematicalModeling. Course may be repeated up to three times for a maximum of nine semester credit hours.

IV.   Learning Objectives

Students will learn issues, techniques, and/or applications related to the specific topic of the course section.

V.    Academic Integrity

Students and employees at Oakton Community College are required to demonstrate academic integrity and follow Oakton's Code of Academic Conduct. This code prohibits:

• cheating,
• plagiarism (turning in work not written by you, or lacking proper citation),
• falsification and fabrication (lying or distorting the truth),
• helping others to cheat,
• unauthorized changes on official documents,
• pretending to be someone else or having someone else pretend to be you,
• making or accepting bribes, special favors, or threats, and
• any other behavior that violates academic integrity.

There are serious consequences to violations of the academic integrity policy. Oakton's policies and procedures provide students a fair hearing if a complaint is made against you. If you are found to have violated the policy, the minimum penalty is failure on the assignment and, a disciplinary record will be established and kept on file in the office of the Vice President for Student Affairs for a period of 3 years.
Details of the Code of Academic Conduct can be found in the Student Handbook.

VI.   Sequence of Topics

The outline of topics for course sections is, naturally, contingent on course content.  What follows is an example of a course outline that is based upon an Introduction to Mathematical Modeling.

A. Optimization Models
    1. One-Variable Optimization
        a. Sensitivity Analysis
        b. Robustness
    2. Multivariable Optimization
        a. Unconstrained Optimization
        b. Lagrange Multipliers
    3. Computational Methods for Optimization
        a. Single and Multivariable Optimization
        b. Linear Programming
        c. Discrete Optimization
B. Dynamic Models
    1. Steady-State Analysis
    2. Dynamical Systems
    3. Eigenvalue Methods
        a. Discrete Systems
        b. Phase Portraits
    4. Simulation of Dynamic Models
        a. Continuous-Time Models
        b. Euler’s Method
        c. Chaos and Fractals
C. Probability Models
    1. Discrete Models
    2. Continuous Models
    3. Stochastic Models
        a. Markov Chains
        b. Linear Regression
    4. Simulation of Probability Models
       a.    Monte Carlo Methods
       b.    Markov Property

VII.  Methods of Instruction

Lectures, class discussions, individual and group projects and use of  calculators or computers where applicable.
Course may be taught as face-to-face, media-based, hybrid or online course.

VIII. Course Practices Required

Reading of the text and/or handouts is required as a reference to the materials and the techniques under study.

IX.   Instructional Materials

Note: Current textbook information for each course and section is available on Oakton's Schedule of Classes.

Vary with individual sections.  Will include texts and/or handouts.

X.    Methods of Evaluating Student Progress

(To be determined and announced by the instructor)

Methods of presentation can include lectures, class discussions, and individual and group assignments. Calculators / computers will be used when appropriate.

XI.   Other Course Information

Individual instructors will establish and announce specific policies regarding attendance, due dates and make-up work, incomplete grades, etc.

If you have a documented learning, psychological, or physical disability you may be entitled to reasonable academic accommodations or services. To request accommodations or services, contact the Access and Disability Resource Center at the Des Plaines or Skokie campus. All students are expected to fulfill essential course requirements. The College will not waive any essential skill or requirement of a course or degree program.