This course is an introduction to computer science and I do not expect students to have any programming experience prior to taking this course. Students will learn how to problem solve, program in Python, and the basics of many different subfields of computer science such as artificial intelligence, human computer interaction, and computer hardware.

I hope that students will acquire the ability to think through problems, as well as to solve them in code. Ideally, students will leave the course with an understanding that there is more to computer science than programming—they will become familiar with the software engineering process. Since computer science can be useful in conjunction with essentially any other field, I want students to start to think how the course may be useful to other disciplines they are learning about at Loyola.

At Loyola there is a clear value on breadth of knowledge, which is excellent for science majors. Our students graduate with strong interpersonal skills, as well as writing and communication skills, that students from other universities may not always acquire. In addition, students from outside of sciences may take classes in computer science and apply it to their own field, preparing them for careers that may not exist yet but will exist by the time they graduate. It's great to be able to help students see how everything is interconnected, and know that they will be taking courses outside of science and math. In upper-level courses, you can expect that students have a certain level of knowledge outside of their major, which can then be leveraged. It's also wonderful to teach somewhere that values the whole person, and teaching in the Messina program has allowed me to help students adjust to college in more than academics, and get to know them better. Although this course is not a service learning course, I love Loyola’s emphasis on community service and being able to encourage students to get involved in the community.

This particular course focuses on data science. In the second half of the semester, once students have learned enough problem solving and programming skills, they work on projects that analyze real world data to answer interesting questions. Example problems include looking at diversity and segregation of cities, creating recommendation systems like Amazon or Netflix, and analyzing political tweets. The goal is to help students not only understand how to analyze data, but also to see how computer science can be applied to problems in many other disciplines and is relevant to our lives. These skills should be useful to them long after taking the course, no matter what major they later choose.

I hope students will discover that Statistics is everywhere. Whatever you do you will encounter statistics.

At Loyola, faculty members are available to students and are willing to spend time to help students succeed.

We will describe data using various graphical and numerical approaches to understand what is going on.

We do some “fun” statistical activities during enrichment sessions. The first is Deming’s Red Bead experiment which simulates a manufacturing work environment. The activity introduces control charts, a method used in quality control. The second activity is “Trashball.” Students attempt to toss a ball into a trash can. The probability of getting the ball into the trash can is modeled using logistic regression.