GRADUATE CERTIFICATE IN AI AND MACHINE LEARNING
Step into the future of technology with Villanova's Certificate in AI and Machine Learning, a dynamic, flexible and highly applicable program designed for students and professionals seeking a strong foundation in this rapidly evolving field.
Gain expertise collecting and processing data; selecting, training and evaluating AI/ML models; and deploying them within professional settings. With an emphasis on practical solutions, students will learn to apply AI in ways directly beneficial to organizations and society. It emphasizes both technical skills and ethical considerations, addressing the need for responsible AI/ML progress. Join the next wave of AI/ML innovators!
CERTIFICATE DETAILS
The Graduate Certificate in AI and Machine Learning is designed to give students the knowledge to specialize in artificial intelligence and machine learning (AI/ML) as a career or to continue with advanced study in the field. It will provide a basic understanding of the tools and methods of AI/ML, with an emphasis on practical solutions to real problems. Students will learn to apply AI/ML in ways directly beneficial to organizations and society. It emphasizes both technical skills and ethical considerations, addressing the need for responsible AI/ML applications.
Besides meeting the general requirements for admission to Graduate Studies, an applicant should have a bachelor's degree in computer science, engineering, mathematics, statistics or a related field. Applicants with a bachelor's degree in another area who have strong tehcnical backgrounds will also be considered. Experience with computer programming is required. Background in linear algebra (MAT 3400) and statistics (MAT 2310) is helful, however deficiiences in these requirements can be made up in course.
Program Objectives:
- Develop understanding of foundations that underpin AI/ML techniques.
- Develop practical skills in using tools and AI/ML models for data processing and mining.
- Instill understanding of ethical considerations and responsible AI/ML practices.
Key learning goals for the program include:
- Gain proficiency in key machine learning algorithms, including supervised, unsupervised and reinforcement learning.
- Learn to preprocess data and perform data analysis.
- How to evaluate model performance, train models and select models for a given task.
- Learn about bias in machine learning and accountability in AI/ML systems.
The degree requirements are made up of five 3-credit courses. Four courses are required:
- CSC 8000 Foundations of Algorithms and Data Structures
- CSC 8491 Data Mining and Data Visualization
- CSC 8515 Machine Learning
- CSC 8575 Ethics and Computer Science
Students must also complete one elective course. The current list of approved electives is:
- CSC 8520 Artificial Intelligence
- CSC 8525 Computer Vision
- CSC 8550 Computing for Data Science
- CSC 9025 Grand Challenges of Computing (assuming pertinent area of study)
Also available to fulfill the elective requirement are approved Special Topics courses (CSC 9010), such as the following (all offered in recent years):
- Large Language Models
- Natural Language Processing
- Health Informatics Decision Support Systems
Students could also use Statistics courses as electives, such as:
- STAT 7500 Statistical Programming
- STAT 8400 Data Mining and Predictive Analysis
- STAT 8406 Regression Methods