Class Schedule
Fall 2024
Spring 2025
Fall 2025
Spring 2026
CS5100: Foundations of Artificial Intelligence
Introduces the fundamental problems, theories, and algorithms of the artificial intelligence field. Required core class.
Grade: A
CS5800: Algorithms
Focuses on algorithmic design paradigms and techniques for analyzing the correctness, time, and space complexity of algorithms. Required core class.
Grade: A-
​
CS6140: Machine Learning
Provides a broad look at a variety of techniques used in machine learning and data mining, and also examines issues associated with their use.
Grade: A-
DS5230: Unsupervised Machine Learning and Data Mining
Introduces unsupervised machine learning and data mining, which is the process of discovering and summarizing patterns from large amounts of data, without examples of data with a known outcome of interest.
Grade: A
​
Semester GPA: 3.83
Cumulative GPA: 3.83
Semester GPA: TBD
Cumulative GPA: TBD
CS5010: Programming Design Paradigm
Introduces modern program design paradigms. Starts with functional program design, introducing the notion of a design recipe.
Grade: TBD
CS7150: Deep Learning
Introduces deep learning architectures, training methods, and applications in vision and NLP, assuming prior knowledge of machine learning and math fundamentals.
Grade: TBD
​
Semester GPA: TBD
Cumulative GPA: TBD
Semester GPA: TBD
Cumulative GPA: TBD
CS5170: Artificial Intelligence for Human-Computer Interaction*
Offers an overview of the wide range of AI techniques that exploit knowledge of the domain and humans to facilitate interaction between humans and systems, mediate human-human interaction, leverage humans to improve system performance, and promote beneficial outcomes at the social and individual level.
Grade: TBD
CS5335: Robotic Science and Systems or
CS5180: Reinforcement Learning **
​
Official Northeastern Curriculum Page
* The class is a program requirement. Anticipated semester. ** This class is an elective. Anticipated class and semester.