Program Overview

Artificial Intelligence Certificate

Program Type

• Certificate

Format

• On Campus

Estimated Time to Complete

• 1-2 semesters

Credit Hours

• 12

Program Description

Supplement your degree by learning more about the expanding field of artificial intelligence. Artificial Intelligence is playing a larger role in our everyday lives, and this certificate will bolster your resume by giving you a basic understanding of how AI works and its future possibilities.

Requirements

• Software Development for Artificial Intelligence (3 hrs)
  • New paradigms for developing software are needed to create and manage systems with AI capabilities, particularly for practitioners without extensive programming experience. Students in this course will be taught how to leverage available artificial intelligence APIs flexibly and reliably through a series of demo-driven tasks. Additionally, as data management is integral to AI system development, an emphasis will be made to collect and process data for AI system training and testing.
• Introduction to Machine Learning (3 hrs)
  • Theory and practice of machine learning. Linear regression, logistic regression, decision trees, neural network learning, support vector machines, kernel methods, bagging, boosting, random forests, ensemble learning, deep learning, unsupervised learning including k-means and hierarchical agglomerative clustering, semi-supervised learning, active learning, and reinforcement learning. Practical applications of machine learning algorithms. Topics in experimental design and computational learning theory.
• Intro to Big Data and Data Science (3 hrs)
  • Introduction to Big Data and Data Science including an overview of the field, technical challenges, computational approaches, practical applications, structured and unstructured data processing, empirical methods in computer science, data analytics and learning, data visualization, privacy and ethics. Emphasis will be on Big Data and its effect on other topics within Data Science, its technical characteristics, and state-of-the-art Big Data analytics architectures and tools.
• Applied Artificial Intelligence (3 hrs)
  • Core concepts and terminology in artificial intelligence will be introduced to understand the taxonomy of AI applications - the relationships between the tools and frameworks available for intelligent, data-driven decision making. This will include a demo-driven introduction to machine learning, with general principles of powerful predictive models discussed and the role of unsupervised and semi-supervised learning techniques in powering many state-of-the-art decision systems.

Related Programs

• General Engineering Technology Minor
• Cybersecurity Minor

Similar Areas of Study

• Data Analytics & Information
• STEM

Department

• Department of Computer Science and Engineering

Location

• Discovery Park, Room F201