Data’s Untold Stories: An Introduction to Computer Science (CS201)
What stories are data itching to tell us? How do we discover those stories and share them with the world? Students in this course will learn how to solve interesting and relevant data science problems using the Python programming language. Students will also gain insights into major areas of computer science, including software engineering, computer hardware, artificial intelligence, and ethical and societal issues in computing. No prior computer science knowledge is expected. Satisfies one math/science core requirement.
Dr. Roger Eastman specializes in visual computing, teaching courses in graphics for video games, computer art and scientific simulation for over 25 years. In research he has worked with Johns Hopkins Wilmer Institute staff on medical imaging for the diagnosis of glaucoma; with NASA researchers on the analysis of Earth and Mars satellite images; and currently with NIST staff on vision for smart manufacturing robotics. His 2010 Cambridge Press "Image Registration for Remote Sensing" received the Alpha Sigma Nu book award in science.
Introduction to Statistics: Stories Data Tell (ST210)
Consumers are continuously inundated with statistical information, from which car to purchase, which candidate one should vote for, and whether or not a new cancer treatment is effective. To understand the story the data is telling, a sound background in statistics is necessary. This course will introduce students to the application of statistics in diverse fields. We will extract the story from data using graphical and numerical methods as well as statistical inference procedures, and use the computer to efficiently perform computations and construct graphs. Statistical methods are motivated through real data sets. This is a non-calculus-based course covering descriptive statistics, simple linear regression, normal, binomial, and sampling distributions, estimation, and hypothesis testing. The course will use a new approach to understanding statistical inference using the computationally intensive resampling approach.
Students planning on majoring in computer science, mathematics, or statistics are encouraged to take this Messina pairing. Of course, other majors are welcome. These two courses can count as two of the three required science core courses.
Dr. Morrell has a Ph.D. in statistics from the University of Wisconsin-Madison. He had been a faculty member at Loyola over 30 years. In addition to teaching undergraduate statistics, Dr. Morrell works with researchers at the National Institute on Aging to study how various characteristics of people change as they age. He is now also the director of the new Data Science master’s program. Dr. Morrell has been an advisor of first year students for many years.
Patrick Durkin is Assistant Director of Event Services. A Loyola graduate from the class of 2001, Patrick has been working Full Time at the University in the Event Services department for the last 14 years. He is originally from Buffalo, NY (Go Sabres!) where he graduated from Canisius High School. He spends as much time as he can with his two young daughters, who are already looking forward to being part of Loyola’s classes of 2031 and 2034!