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# MATH202 Differential Equations

Course Code Course Title Weekly Hours* ECTS Weekly Class Schedule
T P
MATH202 Differential Equations 3 2 6 Tuesday 9.00 - 11.00, Thursday 9.00 - 10.00
Prerequisite MATH102 It is a prerequisite to
Lecturer Seyednima Rabiei Office Hours / Room / Phone
Monday:
10:00-12:00
Tuesday:
13:00-15:00
Wednesday:
13:00-15:00
Friday:
13:00-15:00
A F2.4
E-mail nrabiei@ius.edu.ba
Assistant Assistant E-mail
Course Objectives Differential Equations are the language in which the laws of nature are expressed. Understanding properties of solutions of differential equations is fundamental to much of contemporary science and engineering. Ordinary differential equations deal with functions of one variable, which can often be thought of as time. The goal of the course is to give students an understanding of the fundamental principles of ordinary differential equations and their applications to everyday life and technology and to develop an appreciation of ordinary differential equations topics as a human Endeavor, thereby enriching the students' experience of life. The course will provide a reasonably broad perspective of modeling using first order ordinary differential equations, and model solving, using them in the professional life, as well as further graduate studies in computer engineering, and other fields of engineering and after taking this course, students will be able to deal with the problems of engineering and science by the use of higher order ordinary differential equations and to develop an appreciation of ordinary differential equations modeling as a creative activity, using informed intuition and imagination to create an understanding of the beauty, simplicity and symmetry in the calculated nature.
Textbook C. Henry Edwards, David E. Penney. Elementary Differential Equations with Boundary Value Problems. Dennis G. Zill. A First Course in Differential Equations with Modeling applications. Shepley l. Ross. Differential Equations. M. Can, E.Tacgin, R.Koker, c. Sarioglu. Differential Equations.
Learning Outcomes After successful  completion of the course, the student will be able to:
1. Model natural phenomena by using first order ordinary differential equations, first second ordinary differential equations, and linear first order systems of ordinary differential equations.
2. Solve second order ordinary differential equations by using series, and Laplace transforms.
3. Solve second order systems of ordinary differential equations by using linear algebra methods, and Laplace transforms.
Teaching Methods Class discussions with examples. Active tutorial sessions for engaged learning and continuous feedback on progress.
WEEK TOPIC REFERENCE
Week 1 Introduction to Differential Equations.
Week 2 The General Solution of a Differential Equation.
Week 3 First Order Differential Equations. Separable Equations. Linear Equations.Exact Equations.
Week 4 Solutions by Substitutions. Modeling with First Order Differential Equations.
Week 5 Higher Order Differential Equations. Preliminary Theory-linear Equations.
Week 6 Initial Value and Boundary Value Problems. Homogeneous Equations.
Week 7 Non-Homogeneous Equations. Reduction of Order. Homogeneous linear Equations with Constant Coefficients
Week 8 Power Series Methods. Review of Power Series. Series solution Near Ordinary Points.
Week 9 Solutions about Singulars Points. Special Functions.
Week 10 Laplace Transform Methods.
Week 11 Linear systems of linear first order Differential Equations. Homogeneous linear systems
Week 12 Distinct Real Eigenvalues. Repeated Eigenvalues. complex Eigenvalues.
Week 13 Non-Homogeneous Linear system.
Week 14 Partial Differential Equations.
Week 15 Review
 Assessment Methods and Criteria Evaluation Tool Quantity Weight Alignment with LOs Final Exam 1 30 Semester Evaluation Compenents Midterm Exam 1 35 Quizes 3 35 ***     ECTS Credit Calculation     ***
 Activity Hours Weeks Student Workload Hours Activity Hours Weeks Student Workload Hours Lecture Hours 3 15 45 Midterm and quiz study 5 1 5 Active tutorials 2 13 26 Final Exam study 12 1 12 Home study 4 13 52 Quiz Study 5 2 10 Total Workload Hours = 150 *T= Teaching, P= Practice ECTS Credit = 6 Course Academic Quality Assurance: Semester Student Survey Last Update Date: 19/03/2020 