Artificial Intelligence - Albright College
Source: https://www.albright.edu/academics/undergraduate-programs/artificial-intelligence
Archived: 2026-04-23 17:12
Artificial Intelligence - Albright College
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Artificial Intelligence
Design intelligent systems. Shape an AI‑powered world.
Albright’s AI major prepares students to lead the rapidly expanding world of machine learning, automation, and intelligent decision-making. Students gain strong computational and mathematical foundations while exploring cutting-edge AI applications.
About the Program
The curriculum blends computer science, statistics, and advanced AI concepts, supported by faculty who engage the community through AI outreach and education.
Hands-On Learning
Students engage in hands-on machine learning projects, design AI systems in the capstone sequence, and gain industry experience through internships.
Program Goals
Course Requirements
Opportunities
Faculty
Algorithmic Problem Solving:
Solve problems within computer science and in other domains using computational tools.
Ethical Collaboration & Technical Communication:
Work on integrated teams to deliver software grounded in ethical conduct and an understanding of computing’s societal impacts. Be able to explain technical concepts to a variety of stakeholders.
Systems Thinking:
Understand how the multiple layers of the hardware and software stack work in concert to support modern applications.
Analytical and Mathematical Reasoning:
Apply mathematical and logical reasoning, including discrete mathematics and statistics, to analyze computational problems.
Data Engineering:
Collect, clean, and manage large data sets, and design pipelines that support training and deployment of AI systems.
Artificial Intelligence Major Curriculum
Major Requirements
CSC 141 Foundations of Computer Science I
CSC 142 Foundations of Computer Science II
CSC 210 Data Structures & Algorithms
CSC 280 Computer Ethics
CSC 300+ Advanced Computer Science Elective
CSC 382 Computer Science Internship
CSC 390 Data Science
CSC 480 Introduction to Artificial Intelligence
CSC 481 Machine Learning
CSC 482 Deep Learning
CSC 483 Advanced Topics in AI
CSC 493 Artificial Intelligence Capstone
MAT 110 Elementary Statistics
MAT 131 Calculus and Analytical Geometry I
MAT 250 Foundation of Mathematics
MAT 320 Linear Algebra
Internships and Career Support
Students can connect with the
Career Development Center
to find internships where they can apply learned skills from their Artificial Intelligence degree.
ACRE Undergraduate Research
Students in any major can engage in interdisciplinary undergraduate research through the
Albright Creative Research Experience (ACRE)
, partnering with faculty mentors to pursue independent research or creative projects and present their work beyond the classroom.
Don Baldridge , M.F.A.
Assistant Professor of Computer Science
Suzanne Fellows
Adjunct Faculty
Dave Kaul , M.F.A.
Assistant Professor of Computer Science
David Kopec , M.S., M.B.A.
Chair / Professor / Acad Program Cood, Info Systems, ADP
Kate Perkins
Adjunct Faculty
Bethany Riley
Adjunct Faculty
Ernest Tidball
Adjunct Faculty
Curriculum Highlights
Data Structures & Algorithms
Data Science and Linear Algebra
Machine Learning & Deep Learning
AI Capstone and required internship
Skip To Main Content
Artificial Intelligence
Design intelligent systems. Shape an AI‑powered world.
Albright’s AI major prepares students to lead the rapidly expanding world of machine learning, automation, and intelligent decision-making. Students gain strong computational and mathematical foundations while exploring cutting-edge AI applications.
About the Program
The curriculum blends computer science, statistics, and advanced AI concepts, supported by faculty who engage the community through AI outreach and education.
Hands-On Learning
Students engage in hands-on machine learning projects, design AI systems in the capstone sequence, and gain industry experience through internships.
Program Goals
Course Requirements
Opportunities
Faculty
Algorithmic Problem Solving:
Solve problems within computer science and in other domains using computational tools.
Ethical Collaboration & Technical Communication:
Work on integrated teams to deliver software grounded in ethical conduct and an understanding of computing’s societal impacts. Be able to explain technical concepts to a variety of stakeholders.
Systems Thinking:
Understand how the multiple layers of the hardware and software stack work in concert to support modern applications.
Analytical and Mathematical Reasoning:
Apply mathematical and logical reasoning, including discrete mathematics and statistics, to analyze computational problems.
Data Engineering:
Collect, clean, and manage large data sets, and design pipelines that support training and deployment of AI systems.
Artificial Intelligence Major Curriculum
Major Requirements
CSC 141 Foundations of Computer Science I
CSC 142 Foundations of Computer Science II
CSC 210 Data Structures & Algorithms
CSC 280 Computer Ethics
CSC 300+ Advanced Computer Science Elective
CSC 382 Computer Science Internship
CSC 390 Data Science
CSC 480 Introduction to Artificial Intelligence
CSC 481 Machine Learning
CSC 482 Deep Learning
CSC 483 Advanced Topics in AI
CSC 493 Artificial Intelligence Capstone
MAT 110 Elementary Statistics
MAT 131 Calculus and Analytical Geometry I
MAT 250 Foundation of Mathematics
MAT 320 Linear Algebra
Internships and Career Support
Students can connect with the
Career Development Center
to find internships where they can apply learned skills from their Artificial Intelligence degree.
ACRE Undergraduate Research
Students in any major can engage in interdisciplinary undergraduate research through the
Albright Creative Research Experience (ACRE)
, partnering with faculty mentors to pursue independent research or creative projects and present their work beyond the classroom.
Don Baldridge , M.F.A.
Assistant Professor of Computer Science
Suzanne Fellows
Adjunct Faculty
Dave Kaul , M.F.A.
Assistant Professor of Computer Science
David Kopec , M.S., M.B.A.
Chair / Professor / Acad Program Cood, Info Systems, ADP
Kate Perkins
Adjunct Faculty
Bethany Riley
Adjunct Faculty
Ernest Tidball
Adjunct Faculty
Curriculum Highlights
Data Structures & Algorithms
Data Science and Linear Algebra
Machine Learning & Deep Learning
AI Capstone and required internship