Introductory numerical analysis with Python (undergraduate).

## Course description

This is an introductory course in numerical analysis. In this course, we will learn how to use Python, one of the most popular programming languages in the world. Over the past decade, Python has been gaining popularity among scientific and academic communities in particular.

After learning the syntax of Python, we will quickly cover the basics of numpy and matplotlib, both of which are essential tools for numerical analysis. Equipped with these tools, we will then learn the basics of numerical analysis and its applications to economics.

Class will meet on Fridays from 12:50 to 14:20.

## Prerequisites

Nothing in particular. But some background knowledge of economics and mathematics would be useful.

From the second week of this course, I presume that you have already installed Python in your computer along with the following packages:

- matplotlib
- Numpy
- Scipy
- iPython (optional)

There are various Python distributions available. Among them, I would recommend Anaconda, free Python distribution for data processing and scientific computing. Anaconda includes all the packages mentioned above and many more.

It is not that Anaconda is necessary for this course, but using Anaconda distribution is probably the easiest way to set up the Python environment for scientific computing.

It might be worth noting that if you use mac or linux, chances are that Python is already pre-installed in your computer. The pre-installed version, however, is not sufficient for this course.

Please go to Anaconda Install. Follow the instruction there and set up the Python environment if you have not done so yet.

## Textbooks and course website

- Campbell J., P. Gries, J. Montojo, and G. Wilson,
*Practical programming: an introduction to computer science using Python 3*, Pragmatic Bookshelf, 2013. - Kiusalaas J.,
*Numerical methods in engineering with Python 3*, Cambridge University Press, 2013. - Course website