MAT 290 GENERIC COURSE SYLLABUS

Vary depending on a specific topic.

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 Mathematical Modeling. Course may be repeated up to three times for a maximum of nine semester credit hours.

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

Students, Faculty and administration 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,
• making unauthorized changes in official documents,
• pretending to be someone else or having someone else to 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 with a fair hearing if a complaint is made. 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.

	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 Systems 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

(To be completed by instructor)

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

(To be completed by instructor)

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

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

Required Materials:

X.

(To be determined and announced by the instructor)

Quizzes, examinations, final examination, individual and group assignments.

XI.

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 ASSIST office in Instructional Support Services. 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.