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2022-2023 Undergraduate and Graduate Bulletin (with addenda) 
    
    Mar 28, 2024  
2022-2023 Undergraduate and Graduate Bulletin (with addenda)

Emerging Technologies: Concentration in Machine Learning & Artificial Intelligence, M.S.


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M.S. Emerging Technologies


Build Your Own Master’s Degree

In the Emerging Technologies Master of Science program at NYU Tandon, students have the freedom to design a unique curriculum engineered by them to match their interests and professional aspirations.

This degree is ideal for individuals who intend to advance their careers within various tech roles across multiple industries. Explore cross-functional and high-value knowledge areas including machine learning & AI, user experience & design, wireless, cybersecurity, innovation & change management, robotics, data science, urban informatics, and software engineering.

In this 30-credit program, students have the autonomy to select concentrations* and courses from across several academic departments at Tandon. Students are free to optimize their studies by designing their own path, exploring the intersections across engineering disciplines that best fit their professional passions.

*Students may switch concentration once during the M.S. in Emerging Technologies program, but only after one semester in the original plan of study, and not in the last semester.

Core Courses (9 credits)


Students will select at least three courses (9 credits) from the following selection of Machine Learning & Artificial Intelligence courses.

Capstone (3 credits)


Students have two choices to complete the capstone course requirement.

Capstone Option 1: ECE-GY 7143 Advanced Machine Learning  3 Credits

Students will complete a project proposing, demonstrating, and evaluating a new theoretical or practical method addressing a notable issue in deep learning. Examples include compression of neural networks, optimization methods, multi-label classification, and bounding.

OR

Capstone Option 2: CS-GY 6943 Artificial Intelligence for Games   3 Credits

Students will work on a comprehensive project with the goal of producing research that could be publishable in CIG, AIIDE, FDG, or other core venues. Projects could include work such as a new game-playing algorithm, a new way of using an existing algorithm in a game, AI for your existing game, a new procedural generation algorithm, an analysis of how use PCG in various types of games, a characterization of a problem, a new user study, etc.

Emerging Technologies Electives (18 credits)


Students may choose electives from the following lists that best suit their own interests and academic and professional goals. Other courses, not on this list, may be chosen with advisor approval. Note: courses that have been used to fulfill the core or capstone requirements do not also count towards the elective credits.

Sample Study Plans for Emerging Technologies


Full-Time Study Plan

1st Semester Credits 2nd Semester Credits
Core Course 3 Core Course 3
Elective 3 Elective 3
Elective 3 Elective 3
3rd Semester Credits 4th Semester Credits
Core Course 3 Capstone 3
Elective 3    
Elective 3    

Part-Time Study Plan

1st Semester Credits 2nd Semester Credits
Core Course 3 Core Course 3
Elective 3 Elective 3
3rd Semester Credits 4th Semester Credits
Core Course 3 Elective 3
Elective 3 Elective 3
5th Semester Credits    
Capstone 3    
Elective 3    

 

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