KECD 2260 - PROGRAMMING COURSE

The main purpose of this course is to introduce you to computer programming in a practical way. By the end of the course, you should be able to solve problems by writing computer code from scratch.

To achieve this goal, the course will sometimes be very applied - write and plot a simple function - and sometimes more theoretical – how can your computer even possibly understand this function.

Although this course is mainly targeted to beginners, people with little or no previ- ous experience with computer programming, the level of complexity will steadily rise throughout the semester, such that even people with intermediate knowledge might find some interest in the class.

We will focus on two programming languages:

• R and (if possible) Julia.

The first part of the course will be based on R due to its user-friendliness. Moreover, R is fantastic for people working with data.

Towards the end of the semester, we will switch to Julia to cover more advanced topics in programming, if time permits.

The two languages are relatively similar, so going from one to another should not cause any trouble. Note that this course is not on numerical methods, nor on applied econometrics, even though we might deal with econometrics example.

Little to no programming experience is required for this course.

However, you will need to come to class with your laptop, and some softwares installed on it:

• R (v.3 or later) and RStudio
• Julia (v1.0 or later)
• Git + create a Github account

For the Windows lovers:

a Unix emulator (like Gow or Cygwin). Please do not install those for now, unless you absolutely know what you are doing. I will get back to you before the semester starts with precise instructions on how to install these softwares.

Additionally, I will be holding some office hours to help you with those installs.

The course will be made of three sections of unequal lengths

1 Introduction: How a computer ”thinks”? How to interact with it? How to work collaboratively on programming projects?

2 Programming: the basics in R. Introduction to data types and structures, logical operators, functions, data analysis, plots, input/output, etc.

3 Advanced programming in Julia: Introduction to type systems, package manage- ment, code profiling and optimization, etc.

This course will not be graded and you will not receive any credit for it. Nevertheless, I still encourage you to take it seriously, as :

knowing how to program efficiently is key in nowadays research, and this can be learn only by practicing frequently

professors in future classes will expect you to master the content of this course. Throughout the semester, you will have to complete

weekly problem sets, if possible alone

(if time permits) a four-hour hackathon, by teams of two or three students