[MUSIC] Welcome to Module 2, this module will focus on teaching you how to write basic Python programs. One of the events that takes place every year at Memorial Stadium is the finish or conclusion of the Illinois Marathon. This event attracts runners from all over the world, and handling the logistics for this race, and the race results, can be challenging. The race actually concludes right behind me. In this module, you will learn the basic skills needed to write simple scripts that can simplify the types of challenges faced by those organizing the Illinois Marathon. Note, this course is not designed to train you to become a computer programmer. Instead, you will learn to use Python and scripts to perform data and statistical analysis. You will learn a lot about Python in this and subsequent courses. But the focus is on using Python to gain insight from data. First, you will read about why accounting students should learn to code. Without giving way the details, there are several reasons. First, data analytics is best done by writing scripts to learn from data. Second, even if you aren't programming, knowing the basic concepts for writing a program allows you to communicate more effectively with those who do program. You may develop scripts which give guidance to how to infer insight from data. And those scripts may be passed on to professional programmers or teams of programmers, who turn those into a finished product. Third, by learning how to write a computer program, you will learn different approaches to an analytics task. Now, I want to share an anecdote about a student who's taken this course from be before. This student was part of a Hackathon team and I was a judge for this Hackathon this past February. Afterwards, the student told me that all the other students on the group didn't realize this student was an accounting major. They all assumed that this student knew programming sufficiently to be an engineering student. Needless to say, that made the student feel very good about her analytic skills. And the fact that she had these skills and could use them to analyze data helped her build her future career. So what are the steps that we're going to cover? First, we'll cover basic data structures, including the list, the string, the tuple, and the dictionary. When I first started using Python about 20 years ago, these data structures were very important, and made me really enjoy programming in Python. I think you'll find the same thing, and the reason is because they allow you to aggregate basic data like integers, real numbers, or characters into larger objects that can be easily manipulated. And since they are used in many places, understanding this basic data structures is important, especially how to create them, how to select or slice subsets of data from them, and how to loop over them to perform some complex operation. Second, we will introduce the concept of a function. A function simply packages some level of code together into a reusable unit. So you will learn how to write a function, learn how to use them, and then how to change results inside them to return different data. Third, we will introduce some basic programming concepts that enable conditional branching and iteration. Conditional branching is simple. When you approach a street corner, you have to decide do you go straight, do you turn left, do you turn right, or do you back up? Making that decision is what's known as a conditional branch. Based on a particular value, you may choose to go right or left. Iteration, likewise, is where you perform some operation repeatedly, and you need to do so until a certain condition occurs. Taken together, these two concepts form the foundation for programming in Python. And understanding them, as well as how to write functions and use these basic data structures, will allow you to write simple data analytics scripts in Python. I hope you're excited to learn these skills and to put them to use in this course, good luck. [SOUND]
