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-
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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
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Semester GPA: 3.83
Cumulative GPA: 3.83
Semester GPA: TBD
Cumulative GPA: TBD
CS5130: Applied Programming and Data Processing for AI
Presents an in-depth exploration of programming paradigms, mathematical foundations, and computational techniques essential for scientific computing and data-driven applications.
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
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Semester GPA: TBD
Cumulative GPA: TBD
Semester GPA: TBD
Cumulative GPA: TBD
CS5170: AI Capstone*
Offers students a culminating experience through one or more projects to apply key concepts learned throughout their program in the core and elective courses.
Grade: TBD
CS7140: Advanced Machine Learning**
Covers topics in advanced machine learning. Presents materials in the current machine learning literature. Focuses on graphical models, latent variable models, Bayesian inference, and nonparametric Bayesian methods.
Grade: TBD
Official Northeastern Curriculum Page
* The class is a program requirement. Anticipated semester. ** This class is an elective. Anticipated class and semester.