Data Science and Engineering for Discovery and Diversity
Summer I 2023 Featured Program
Led by an initiative from Florida Agricultural and Mechanical University (Florida A & M University, FAMU) one of the historically black colleges and universities (HBCU) in the U.S. and ranked by US News and World Report as the #1 Public HBCU in the U.S., John Cabot University is offering a summer course on introduction to data science.
This introductory project-based learning course in data science provides students with a learning experience in carrying out a tangible data science analysis with a focus on the student’s choice of a real-world problem using pre-existing secondary data. The course includes a critique of the inherent biases of data science itself and their societal implications. The full course description is below.
The collaboration between Florida A & M and JCU is the foundation in building a vibrant international summer program that brings together data science and engineering, diversity, and the humanistic traditions of the liberal arts. This summer program will serve as a focal point for highlighting and discussing the many societal and ethical issues that arise from data science and engineering and artificial intelligence. These topics are already being discussed within the John Cabot University Institute of Future and Innovation Studies.
Past events on data, AI, ethics, and social justice sponsored by the Institute include:
- “Social Justice in Code” a seminar in collaboration with resident and visiting faculty from Florida A&M University, Maryland Institute College of Art, and Indiana University Bloomington. June 7, 2022.
- "Data Ethics of Power: A Human Approach in the Big Data and AI Era" in collaboration with the European think-tank DataEthics.eu, hosted Gry Hasselbalch for a presentation of her latest book (Edward Elgar Publishing, 2022). December 20, 2021.
In support of Florida A & M University’s international education diversity initiative, John Cabot University has established automatic scholarships for students from HBCUs who enroll in any of JCU’s summer (or semester) sessions.
We look forward to seeing you in Rome this summer and invite you to build with us!
CS 212 Introduction to Data Science (Prerequisites: CS 160, MA 100/101)
This course introduces students to the main concepts of data science. It combines statistical, ethics, computational learning theory, pattern recognition, and containerization to create and implement Machine Learning and Deep Learning models for classification and prediction. Such models may have a significant impact on society, as they can be used to automate procedures and extract relevant information from large amounts of data. Students will learn how to detect and correct implicit/explicit bias often found in A.I. and Machine Learning algorithms by assessing the quality and objectivity of training data. This is important to determining validity /veracity of information (such as found in social media) and in threat analysis (as in cybersecurity). The course includes a critique of the inherent biases of data science itself and their societal implications. The course uses project-based learning: students will be guided through the process of formulating and carrying out data science methodology with real-world data, with a focus on open, pre-existing secondary data. Topics covered include descriptive statistics, elementary probability theory, basics of linear algebra, ethics in emerging technology, nonparametric decision-making such as Euclidean distance, nearest neighbor, support vector machine, decision tree, and supervised and unsupervised learning techniques such as neural networks, kernel machines, convolutional networks.
Yohn Jairo Parra Bautista is an Assistant Professor, Computer and Information Sciences Department, College of Science and Technology at Florida Agricultural & Mechanical University. He is a team member initiating research and teaching in data science and engineering and creating and promoting Artificial Intelligence and data science across the curriculum. He is instrumental in developing a project-activated data science and AI REU. His Big Data research interests are in text analysis, Data behavior and its implications in AI and ethics. In 2021 he received a Microsoft USA Data Science Fellowship. He received a PhD in Computational and Data Enabled Science and Engineering from Jackson State University in 2020. Learn more about Prof. Parra Bautista.
Carlos Andres Theran-Suarez is an instructor in the Computer and Information Sciences Department at Florida Agricultural & Mechanical University. He is a team member in the data science and engineering group at FAMU. His research is on developing and implementing machine learning pipelines to solve societal problems involving different types of datasets, such as satellite imagery and healthcare data. His experience includes developing cloud computing infrastructures to analyze a significant volume of data using data science tools such as Hadoop, Hive, and Spark. As a part of his educational activities, he has been part of the development of a data science and AI curriculum with an active-learning modality for REU programs. He is a Ph.D. candidate in Computer and Information Science and Engineering at the University of Puerto Rico-Mayaguez.