25 courses with the subject AIM, each shown exactly as we captured it from the college's catalog, with every element we hold. Where the wording looks broken, that is our reading of the catalog, not the college's text.
Artificial Intelligence (AI) is an interdisciplinary field, integrating knowledge and methods from computer science, mathematics, philosophy, psychology, economics, neuroscience, linguistics, and biology. Intelligent agents mimic cognitive functions to implement intelligent behaviors such
This course focuses on the data structures, data design patterns, algorithms, methods, and best practices for the pre-modeling phases of data science workflows, including problem formulation, gather, analyze, explore, model, and communicate, a
Arguably, most of data science is statistical learning, which requires strong foundational knowledge in probability and statistics. And applying computational methods such as direct s
Algorithms in machine learning and neural networks are built upon a strong foundation of linear algebra. For example, modern recommendation systems
Predictive modeling answers the question, 'What will happen next?' Linear regression and logistic regression are foundational predictive modeling methods, used to pr
In classical programming, answers are obtained from rules and data. In machine learning, rules are obtained from data and answers. The widespread availability and sharing of data, and improv
Data scientists have been able to leverage better algorithms on faster hardware optimized with graphical processing units to deliver improved performance and
The Capstone integrates prior coursework, research, colloquia, and professional experience, and provides the opportunity to synthesize theory with practice in an applied project, thesis, approved inte
Bayesian inference provides powerful tools to model random variables. While Bayesian methods often yield the most accurate theoretical results, historically analytical complexity made it challenging to apply Bayesian methods against less trivial problems. Now, the confluence of
What is needed to convert a promising idea or research into a viable product or service? Bringing successful products to market is an experiential discipline that r
Natural Language Processing lives at the intersection of machine learning, artificial intelligence, and linguistics. It is the key to unlocking vast amounts of human-generated, unstructured data. The increased availability of corpuses of tex
This course provides the opportunity to take on emerging theory, phenomen
As both the volume and the velocity of data increase exponentially, problems in both commerce and research become increasingly reliant on environments with distributed data storage an
This is an advanced course which provides the opportunity to learn s
This course prepares students for hands-on skills in deep reinforcement learning with Python and the PyTorch framework. Combining theory and practice, the course guides
This course covers the foundations of computer vision, from image formation and filtering through modern deep learning approaches for recognition, g
Neural computation spans the full arc from biological brains to engineered systems. This course begins with the anatomy and physiology of the human brain, traces
This course helps students perform tasks associated with the
This course bridges the technical frontier of artificial intelligence with strategic biotech management, preparing future leaders to drive innovation at the intersection of healthcare and technology. Students will gain practical fluency in AI applications across th
The course provides flexibility to learn more about a topic of interest outside of the formal cou
The course will provide a working, business-level grounding in landscape and applications of Artificial Intelligence and Machine Learning (AIML). Students will devel
This course examines how AI transforms markets, industries, organizations, and the structure of work. Students explore the mechanisms through which intelligent systems create shifts in value, alter competit
This course examines how people and AI systems work together as tasks, decisions, and workflows evolve. Students learn the enabling technologies that underlie modern AI tools, how prompting structur
This course introduces how organizations capture, structure, and operationalize knowledge to support AI systems. Students examine how enterprise intelligence architectures store and transmit expertise and how well-designed knowledg
This course examines how humans create, lead, and make decisions in environments transformed by rapidly advancing AI systems. Students explore the aspects of cognition, creativity, and judgment that remain uniquely human, as well as t
Source: Yeshiva University's catalog, linked per course · table learning_unit · CourseShelf publish 61
