This course is mainly intended to provide an introductory-level understanding of numerical analysis and numerical methods. The methods, here, refer to algorithms and techniques that help computers adopt and work with mathematical concepts. This course is well- suited to undergraduate students majoring in engineering or science departments with a special interest in programming. If you are interested in this course but do not fit the above criteria, contact the instructor to start a conversation about whether this course is meant for you.

Learning Resources

• Interactive Lecture notes: The course notes, slides, and assignments are all presented in Jupyter Notebooks to help you easily transiton from lectures to ruuning example codes and turning in your homework assignments. You can write formulas, code and create figures all in the same place. All interactive notebooks are available on Github

• Class Website on Canvas: This is where we share links to class notes, additional reading materials, and important announcements. It is also the place where you will submit your homework. Please visit the class canvas page regularly to stay on top of developments.

• Numerical Methods in Engineering with Python 3 /Jaan Kiusalaas : Textbook, freely available through the university library

Modules

• Introduction to programing with python
• Machine arithmetic
• Function approximation
• Linear systems of equations
• Nonlinear systems of equations
• Numerical differentiation
• Numerical integration
• Solving ordinary differential equations