Emerging Technologies (MS)
Program Description
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 concentrations1 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.
- 1
Students may switch concentrations 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.
Why Choose NYU Tandon?
The Emerging Technologies M.S. program at Tandon allows you to develop your own unique cross-disciplinary path, integrating specialized learning from a variety of online courses and programs. This degree is inherently adaptable to the evolving technology landscape, leading to new opportunities and career advancement within in-demand fields.
Admissions
Admission to graduate programs in the Tandon School of Engineering requires the following minimum components:
- Résumé/CV
- Statement of Purpose
- Letters of Recommendation
- Transcripts
- Proficiency in English
The NYU Tandon Graduate Admissions website has additional information on school-wide admission.
Some programs may require additional components for admissions.
See the program's How to Apply for department-specific admission requirements and instructions.
Program Requirements
The program requires the completion of 30 credits, and students will select one of the following concentrations:
Cybersecurity
| Course | Title | Credits |
|---|---|---|
| Core Courses | ||
| Select three of the following: | 9 | |
| Penetration Testing and Vulnerability Analysis | ||
| Information, Security and Privacy | ||
| Network Security | ||
| Application Security | ||
CS-GY 9223 | (Mobile Security) | |
CS-GY 9223 | (Offensive Security) | |
MG-GY 8213 | ||
| Capstone | ||
| CS-GY 6903 | Applied Cryptography 1 | 3 |
| Emerging Technologies Electives | ||
| Select six of the following: 2 | 18 | |
| Design and Analysis of Algorithms I | ||
| Design and Analysis of Algorithms II | ||
| Foundation of Data Science | ||
| Software Engineering I | ||
| Software Engineering II | ||
| INFORMATION VISUALIZATION | ||
| Programming Languages | ||
| Big Data | ||
| Penetration Testing and Vulnerability Analysis | ||
| Artificial Intelligence I | ||
| COMPUTER VISION | ||
| ALGORITHMIC MACHINE LEARNING AND DATA SCIENCE | ||
| Information, Security and Privacy | ||
| Network Security | ||
| Computer Networking | ||
| Machine Learning | ||
or ECE-GY 6143 | MACHINE LEARNING | |
| Application Security | ||
CS-GY 9223 | (Mobile Security) | |
CS-GY 9223 | (Offensive Security) | |
| Introduction to Applied Data Science | ||
| Machine Learning for Cities | ||
| Innovative City Governance | ||
| Big Data Management & Analysis | ||
| Data Visualization | ||
| Ideation & Prototyping | ||
| Creative Coding | ||
| Mobile Augmented Reality Studio | ||
| SPECIAL TOPICS IN DIGITAL MEDIA (User Experience Design) | ||
| Special Topics in Data Science (Responsible Data Science) | ||
| Digital Communications | ||
| Wireless Communications | ||
| Digital Signal Processing I | ||
| INTERNET ARCHITECTURE & PROTOCOLS | ||
| Data Center and Cloud Computing | ||
| High-Speed Networks | ||
| ECONOMICS AND STRATEGY | ||
| Global Innovation | ||
MG-GY 8213 | ||
| Technology Strategy | ||
| FOUNDATIONS OF ROBOTICS | ||
| ROBOT PERCEPTION | ||
| ROBOT LOCALIZATION AND NAVIGATION | ||
| Robotic Gait and Manipulation | ||
| Total Credits | 30 | |
- 1
In the Capstone course, students will design and build an application that encrypts and decrypts individual files using a password and allows a user to search for keywords in an encrypted file. The program will also be able to detect tampering attempts.
- 2
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.
Data Science
| Course | Title | Credits |
|---|---|---|
| Core Courses | ||
| Select three of the following: | 9 | |
| Foundation of Data Science | ||
| INFORMATION VISUALIZATION | ||
| Big Data | ||
| Special Topics in Data Science (Responsible Data Science) | ||
| Data Center and Cloud Computing | ||
| Capstone | ||
| CUSP-GX 7023 | Applied Data Science 1 | 3 |
| Emerging Technologies Electives | ||
| Select six of the following: 2 | 18 | |
| Design and Analysis of Algorithms I | ||
| Design and Analysis of Algorithms II | ||
| Foundation of Data Science | ||
| Software Engineering I | ||
| Software Engineering II | ||
| INFORMATION VISUALIZATION | ||
| Programming Languages | ||
| Big Data | ||
| Penetration Testing and Vulnerability Analysis | ||
| Artificial Intelligence I | ||
| COMPUTER VISION | ||
| ALGORITHMIC MACHINE LEARNING AND DATA SCIENCE | ||
| Information, Security and Privacy | ||
| Network Security | ||
| Computer Networking | ||
| Machine Learning | ||
or ECE-GY 6143 | MACHINE LEARNING | |
| Application Security | ||
CS-GY 9223 | (Mobile Security) | |
CS-GY 9223 | (Offensive Security) | |
| Introduction to Applied Data Science | ||
| Machine Learning for Cities | ||
| Innovative City Governance | ||
| Big Data Management & Analysis | ||
| Data Visualization | ||
| Ideation & Prototyping | ||
| Creative Coding | ||
| Mobile Augmented Reality Studio | ||
| SPECIAL TOPICS IN DIGITAL MEDIA (User Experience Design) | ||
| Special Topics in Data Science (Responsible Data Science) | ||
| Digital Communications | ||
| Wireless Communications | ||
| Digital Signal Processing I | ||
| INTERNET ARCHITECTURE & PROTOCOLS | ||
| Data Center and Cloud Computing | ||
| High-Speed Networks | ||
| ECONOMICS AND STRATEGY | ||
| Global Innovation | ||
MG-GY 8213 | ||
| Technology Strategy | ||
| FOUNDATIONS OF ROBOTICS | ||
| ROBOT PERCEPTION | ||
| ROBOT LOCALIZATION AND NAVIGATION | ||
| Robotic Gait and Manipulation | ||
| Total Credits | 30 | |
- 1
In the capstone course, students will complete an original research project utilizing open data to address a research question or hypothesis and synthesizing the materials and techniques covered in the curriculum.
- 2
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.
Innovation & Change Management
| Course | Title | Credits |
|---|---|---|
| Core Courses | ||
| MG-GY 6023 | ECONOMICS AND STRATEGY | 3 |
| MG-GY 7953 | Global Innovation | 3 |
| MG-GY 8673 | Technology Strategy | 3 |
| Capstone | ||
| MG-GY 9753 | SELECTED TOPICS IN MANAGEMENT (Strategic Change Management) 1 | 3 |
| Emerging Technologies Electives | ||
| Select six of the following: 2 | 18 | |
| Design and Analysis of Algorithms I | ||
| Design and Analysis of Algorithms II | ||
| Foundation of Data Science | ||
| Software Engineering I | ||
| Software Engineering II | ||
| INFORMATION VISUALIZATION | ||
| Programming Languages | ||
| Big Data | ||
| Penetration Testing and Vulnerability Analysis | ||
| Artificial Intelligence I | ||
| COMPUTER VISION | ||
| ALGORITHMIC MACHINE LEARNING AND DATA SCIENCE | ||
| Information, Security and Privacy | ||
| Network Security | ||
| Computer Networking | ||
| Machine Learning | ||
or ECE-GY 6143 | MACHINE LEARNING | |
| Application Security | ||
CS-GY 9223 | (Mobile Security) | |
CS-GY 9223 | (Offensive Security) | |
| Introduction to Applied Data Science | ||
| Machine Learning for Cities | ||
| Innovative City Governance | ||
| Big Data Management & Analysis | ||
| Data Visualization | ||
| Ideation & Prototyping | ||
| Creative Coding | ||
| Mobile Augmented Reality Studio | ||
| SPECIAL TOPICS IN DIGITAL MEDIA (User Experience Design) | ||
| Special Topics in Data Science (Responsible Data Science) | ||
| Digital Communications | ||
| Wireless Communications | ||
| Digital Signal Processing I | ||
| INTERNET ARCHITECTURE & PROTOCOLS | ||
| Data Center and Cloud Computing | ||
| High-Speed Networks | ||
| ECONOMICS AND STRATEGY | ||
| Global Innovation | ||
MG-GY 8213 | ||
| Technology Strategy | ||
| FOUNDATIONS OF ROBOTICS | ||
| ROBOT PERCEPTION | ||
| ROBOT LOCALIZATION AND NAVIGATION | ||
| Robotic Gait and Manipulation | ||
| Total Credits | 30 | |
- 1
In the capstone course, students will develop and present a comprehensive plan for implementing an organizational change of their choice, including building a case for the change, planning a change management process, and sustaining the change.
- 2
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.
Machine Learning & Artificial Intelligence
| Course | Title | Credits |
|---|---|---|
| Core Courses | ||
| Select three of the following: | 9 | |
| Design and Analysis of Algorithms I | ||
| Artificial Intelligence I | ||
| COMPUTER VISION | ||
| ALGORITHMIC MACHINE LEARNING AND DATA SCIENCE | ||
| Machine Learning | ||
or ECE-GY 6143 | MACHINE LEARNING | |
| Capstone | ||
| Select one of the following: | 3 | |
| Advanced Machine Learning 1 | ||
| Artificial Intelligence for Games 2 | ||
| Emerging Technologies Electives | ||
| Select six of the following: 3 | 18 | |
| Design and Analysis of Algorithms I | ||
| Design and Analysis of Algorithms II | ||
| Foundation of Data Science | ||
| Software Engineering I | ||
| Software Engineering II | ||
| INFORMATION VISUALIZATION | ||
| Programming Languages | ||
| Big Data | ||
| Penetration Testing and Vulnerability Analysis | ||
| Artificial Intelligence I | ||
| COMPUTER VISION | ||
| ALGORITHMIC MACHINE LEARNING AND DATA SCIENCE | ||
| Information, Security and Privacy | ||
| Network Security | ||
| Computer Networking | ||
| Machine Learning | ||
or ECE-GY 6143 | MACHINE LEARNING | |
| Application Security | ||
CS-GY 9223 | (Mobile Security) | |
CS-GY 9223 | (Offensive Security) | |
| Introduction to Applied Data Science | ||
| Machine Learning for Cities | ||
| Innovative City Governance | ||
| Big Data Management & Analysis | ||
| Data Visualization | ||
| Ideation & Prototyping | ||
| Creative Coding | ||
| Mobile Augmented Reality Studio | ||
| SPECIAL TOPICS IN DIGITAL MEDIA (User Experience Design) | ||
| Special Topics in Data Science (Responsible Data Science) | ||
| Digital Communications | ||
| Wireless Communications | ||
| Digital Signal Processing I | ||
| INTERNET ARCHITECTURE & PROTOCOLS | ||
| Data Center and Cloud Computing | ||
| High-Speed Networks | ||
| ECONOMICS AND STRATEGY | ||
| Global Innovation | ||
MG-GY 8213 | ||
| Technology Strategy | ||
| FOUNDATIONS OF ROBOTICS | ||
| ROBOT PERCEPTION | ||
| ROBOT LOCALIZATION AND NAVIGATION | ||
| Robotic Gait and Manipulation | ||
| Total Credits | 30 | |
- 1
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.
- 2
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.
- 3
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.
Robotics
| Course | Title | Credits |
|---|---|---|
| Core Courses | ||
| Select three of the following: | 9 | |
| ALGORITHMIC MACHINE LEARNING AND DATA SCIENCE | ||
| MACHINE LEARNING | ||
or CS-GY 6923 | Machine Learning | |
| FOUNDATIONS OF ROBOTICS | ||
| ROBOT PERCEPTION | ||
| ROBOT LOCALIZATION AND NAVIGATION | ||
| Robotic Gait and Manipulation | ||
| Capstone | ||
| Select one of the following: | 3 | |
| REINFORCEMENT LEARNING AND OPTIMAL CONTROL FOR ROBOTICS 1 | ||
| INTERACTIVE MEDICAL ROBOTICS 2 | ||
| Emerging Technologies Electives | ||
| Select six of the following: 3 | 18 | |
| Design and Analysis of Algorithms I | ||
| Design and Analysis of Algorithms II | ||
| Foundation of Data Science | ||
| Software Engineering I | ||
| Software Engineering II | ||
| INFORMATION VISUALIZATION | ||
| Programming Languages | ||
| Big Data | ||
| Penetration Testing and Vulnerability Analysis | ||
| Artificial Intelligence I | ||
| COMPUTER VISION | ||
| ALGORITHMIC MACHINE LEARNING AND DATA SCIENCE | ||
| Information, Security and Privacy | ||
| Network Security | ||
| Computer Networking | ||
| Machine Learning | ||
or ECE-GY 6143 | MACHINE LEARNING | |
| Application Security | ||
CS-GY 9223 | (Mobile Security) | |
CS-GY 9223 | (Offensive Security) | |
| Introduction to Applied Data Science | ||
| Machine Learning for Cities | ||
| Innovative City Governance | ||
| Big Data Management & Analysis | ||
| Data Visualization | ||
| Ideation & Prototyping | ||
| Creative Coding | ||
| Mobile Augmented Reality Studio | ||
| SPECIAL TOPICS IN DIGITAL MEDIA (User Experience Design) | ||
| Special Topics in Data Science (Responsible Data Science) | ||
| Digital Communications | ||
| Wireless Communications | ||
| Digital Signal Processing I | ||
| INTERNET ARCHITECTURE & PROTOCOLS | ||
| Data Center and Cloud Computing | ||
| High-Speed Networks | ||
| ECONOMICS AND STRATEGY | ||
| Global Innovation | ||
MG-GY 8213 | ||
| Technology Strategy | ||
| FOUNDATIONS OF ROBOTICS | ||
| ROBOT PERCEPTION | ||
| ROBOT LOCALIZATION AND NAVIGATION | ||
| Robotic Gait and Manipulation | ||
| Total Credits | 30 | |
- 1
Students will design and implement a controller for a 2D quadrotor.
- 2
Students will design and simulate a 2-channel teleoperation system for medical robotics application with TDPC.
- 3
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.
Software Development
| Course | Title | Credits |
|---|---|---|
| Core Courses | ||
| Select three of the following: | 9 | |
| Design and Analysis of Algorithms I | ||
| Design and Analysis of Algorithms II | ||
| Software Engineering I | ||
| Software Engineering II | ||
| Programming Languages | ||
| Capstone | ||
| CS-GY 6253 | Distributed Operating Systems 1 | 3 |
| Emerging Technologies Electives | ||
| Select six of the following: 2 | 18 | |
| Design and Analysis of Algorithms I | ||
| Design and Analysis of Algorithms II | ||
| Foundation of Data Science | ||
| Software Engineering I | ||
| Software Engineering II | ||
| INFORMATION VISUALIZATION | ||
| Programming Languages | ||
| Big Data | ||
| Penetration Testing and Vulnerability Analysis | ||
| Artificial Intelligence I | ||
| COMPUTER VISION | ||
| ALGORITHMIC MACHINE LEARNING AND DATA SCIENCE | ||
| Information, Security and Privacy | ||
| Network Security | ||
| Computer Networking | ||
| Machine Learning | ||
or ECE-GY 6143 | MACHINE LEARNING | |
| Application Security | ||
CS-GY 9223 | (Mobile Security) | |
CS-GY 9223 | (Offensive Security) | |
| Introduction to Applied Data Science | ||
| Machine Learning for Cities | ||
| Innovative City Governance | ||
| Big Data Management & Analysis | ||
| Data Visualization | ||
| Ideation & Prototyping | ||
| Creative Coding | ||
| Mobile Augmented Reality Studio | ||
| SPECIAL TOPICS IN DIGITAL MEDIA (User Experience Design) | ||
| Special Topics in Data Science (Responsible Data Science) | ||
| Digital Communications | ||
| Wireless Communications | ||
| Digital Signal Processing I | ||
| INTERNET ARCHITECTURE & PROTOCOLS | ||
| Data Center and Cloud Computing | ||
| High-Speed Networks | ||
| ECONOMICS AND STRATEGY | ||
| Global Innovation | ||
MG-GY 8213 | ||
| Technology Strategy | ||
| FOUNDATIONS OF ROBOTICS | ||
| ROBOT PERCEPTION | ||
| ROBOT LOCALIZATION AND NAVIGATION | ||
| Robotic Gait and Manipulation | ||
| Total Credits | 30 | |
- 1
In the capstone course, students will select a domain area problem, conduct background research, and propose and implement a distributed system as a solution for the problem.
- 2
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.
Urban Informatics
| Course | Title | Credits |
|---|---|---|
| Core Courses | ||
| Select three of the following: | 9 | |
| Introduction to Applied Data Science | ||
| Machine Learning for Cities | ||
| Innovative City Governance | ||
| Big Data Management & Analysis | ||
| Data Visualization | ||
| Capstone | ||
| CUSP-GX 7043 | Civic Analytics and Urban Intelligence 1 | 3 |
| Emerging Technologies Electives | ||
| Select six of the following: 2 | 18 | |
| Design and Analysis of Algorithms I | ||
| Design and Analysis of Algorithms II | ||
| Foundation of Data Science | ||
| Software Engineering I | ||
| Software Engineering II | ||
| INFORMATION VISUALIZATION | ||
| Programming Languages | ||
| Big Data | ||
| Penetration Testing and Vulnerability Analysis | ||
| Artificial Intelligence I | ||
| COMPUTER VISION | ||
| ALGORITHMIC MACHINE LEARNING AND DATA SCIENCE | ||
| Information, Security and Privacy | ||
| Network Security | ||
| Computer Networking | ||
| Machine Learning | ||
or ECE-GY 6143 | MACHINE LEARNING | |
| Application Security | ||
CS-GY 9223 | (Mobile Security) | |
CS-GY 9223 | (Offensive Security) | |
| Introduction to Applied Data Science | ||
| Machine Learning for Cities | ||
| Innovative City Governance | ||
| Big Data Management & Analysis | ||
| Data Visualization | ||
| Ideation & Prototyping | ||
| Creative Coding | ||
| Mobile Augmented Reality Studio | ||
| SPECIAL TOPICS IN DIGITAL MEDIA (User Experience Design) | ||
| Special Topics in Data Science (Responsible Data Science) | ||
| Digital Communications | ||
| Wireless Communications | ||
| Digital Signal Processing I | ||
| INTERNET ARCHITECTURE & PROTOCOLS | ||
| Data Center and Cloud Computing | ||
| High-Speed Networks | ||
| ECONOMICS AND STRATEGY | ||
| Global Innovation | ||
MG-GY 8213 | ||
| Technology Strategy | ||
| FOUNDATIONS OF ROBOTICS | ||
| ROBOT PERCEPTION | ||
| ROBOT LOCALIZATION AND NAVIGATION | ||
| Robotic Gait and Manipulation | ||
| Total Credits | 30 | |
- 1
In the capstone course, students will complete an operational plan for data-based policy and program reform in one government department/agency (e.g., public safety, transportation) or nonprofit (e.g., the Red Cross or Rockefeller Foundation) by creating an overarching reform framework and identifying an area that has potential for significant impact. The plan will include operational and policy detail about existing efforts, assessment of the department or nonprofit, and identification of at least one new technology or platform to be applied. The plan will also include an assessment of community impact; race and equity; and examples of similar reform plans from other agencies, cities, or organizations.
- 2
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.
User Experience & Design
| Course | Title | Credits |
|---|---|---|
| Core Courses | ||
| Select three of the following: | 9 | |
| Ideation & Prototyping | ||
| Creative Coding | ||
| Mobile Augmented Reality Studio | ||
| SPECIAL TOPICS IN DIGITAL MEDIA (User Experience Design) | ||
| Capstone | ||
| DM-GY 6143 | Interaction Design Studio 1 | 3 |
| Emerging Technologies Electives | ||
| Select six of the following: 2 | 18 | |
| Design and Analysis of Algorithms I | ||
| Design and Analysis of Algorithms II | ||
| Foundation of Data Science | ||
| Software Engineering I | ||
| Software Engineering II | ||
| INFORMATION VISUALIZATION | ||
| Programming Languages | ||
| Big Data | ||
| Penetration Testing and Vulnerability Analysis | ||
| Artificial Intelligence I | ||
| COMPUTER VISION | ||
| ALGORITHMIC MACHINE LEARNING AND DATA SCIENCE | ||
| Information, Security and Privacy | ||
| Network Security | ||
| Computer Networking | ||
| Machine Learning | ||
or ECE-GY 6143 | MACHINE LEARNING | |
| Application Security | ||
CS-GY 9223 | (Mobile Security) | |
CS-GY 9223 | (Offensive Security) | |
| Introduction to Applied Data Science | ||
| Machine Learning for Cities | ||
| Innovative City Governance | ||
| Big Data Management & Analysis | ||
| Data Visualization | ||
| Ideation & Prototyping | ||
| Creative Coding | ||
| Mobile Augmented Reality Studio | ||
| SPECIAL TOPICS IN DIGITAL MEDIA (User Experience Design) | ||
| Special Topics in Data Science (Responsible Data Science) | ||
| Digital Communications | ||
| Wireless Communications | ||
| Digital Signal Processing I | ||
| INTERNET ARCHITECTURE & PROTOCOLS | ||
| Data Center and Cloud Computing | ||
| High-Speed Networks | ||
| ECONOMICS AND STRATEGY | ||
| Global Innovation | ||
MG-GY 8213 | ||
| Technology Strategy | ||
| FOUNDATIONS OF ROBOTICS | ||
| ROBOT PERCEPTION | ||
| ROBOT LOCALIZATION AND NAVIGATION | ||
| Robotic Gait and Manipulation | ||
| Total Credits | 30 | |
- 1
In the capstone course, students will complete an appropriate prototype of an interaction design for a client, service, or as a case study in human-computer interaction.
- 2
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.
Wireless & Networking
| Course | Title | Credits |
|---|---|---|
| Core Courses | ||
| Select three of the following: | 9 | |
| Computer Networking | ||
| Digital Communications | ||
| Wireless Communications | ||
| Digital Signal Processing I | ||
| INTERNET ARCHITECTURE & PROTOCOLS | ||
| High-Speed Networks | ||
| Capstone | ||
| ECE-GY 7353 | Network Modeling and Analysis 1 | 3 |
| Emerging Technologies Electives | ||
| Select six of the following: 2 | 18 | |
| Design and Analysis of Algorithms I | ||
| Design and Analysis of Algorithms II | ||
| Foundation of Data Science | ||
| Software Engineering I | ||
| Software Engineering II | ||
| INFORMATION VISUALIZATION | ||
| Programming Languages | ||
| Big Data | ||
| Penetration Testing and Vulnerability Analysis | ||
| Artificial Intelligence I | ||
| COMPUTER VISION | ||
| ALGORITHMIC MACHINE LEARNING AND DATA SCIENCE | ||
| Information, Security and Privacy | ||
| Network Security | ||
| Computer Networking | ||
| Machine Learning | ||
or ECE-GY 6143 | MACHINE LEARNING | |
| Application Security | ||
CS-GY 9223 | (Mobile Security) | |
CS-GY 9223 | (Offensive Security) | |
| Introduction to Applied Data Science | ||
| Machine Learning for Cities | ||
| Innovative City Governance | ||
| Big Data Management & Analysis | ||
| Data Visualization | ||
| Ideation & Prototyping | ||
| Creative Coding | ||
| Mobile Augmented Reality Studio | ||
| SPECIAL TOPICS IN DIGITAL MEDIA (User Experience Design) | ||
| Special Topics in Data Science (Responsible Data Science) | ||
| Digital Communications | ||
| Wireless Communications | ||
| Digital Signal Processing I | ||
| INTERNET ARCHITECTURE & PROTOCOLS | ||
| Data Center and Cloud Computing | ||
| High-Speed Networks | ||
| ECONOMICS AND STRATEGY | ||
| Global Innovation | ||
MG-GY 8213 | ||
| Technology Strategy | ||
| FOUNDATIONS OF ROBOTICS | ||
| ROBOT PERCEPTION | ||
| ROBOT LOCALIZATION AND NAVIGATION | ||
| Robotic Gait and Manipulation | ||
| Total Credits | 30 | |
- 1
In the capstone course, students will complete a project either extending an existing network analysis model or implementing an experimental model in an attempt to reproduce and potentially extend a published result from current research.
- 2
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 Plan of Study
Full-Time
| 1st Semester/Term | Credits | |
|---|---|---|
| Core Course | 3 | |
| Elective | 3 | |
| Elective | 3 | |
| Credits | 9 | |
| 2nd Semester/Term | ||
| Core Course | 3 | |
| Elective | 3 | |
| Elective | 3 | |
| Credits | 9 | |
| 3rd Semester/Term | ||
| Core Course | 3 | |
| Elective | 3 | |
| Elective | 3 | |
| Credits | 9 | |
| 4th Semester/Term | ||
| Capstone | 3 | |
| Credits | 3 | |
| Total Credits | 30 | |
Part-Time
| 1st Semester/Term | Credits | |
|---|---|---|
| Core Course | 3 | |
| Elective | 3 | |
| Credits | 6 | |
| 2nd Semester/Term | ||
| Core Course | 3 | |
| Elective | 3 | |
| Credits | 6 | |
| 3rd Semester/Term | ||
| Core Course | 3 | |
| Elective | 3 | |
| Credits | 6 | |
| 4th Semester/Term | ||
| Elective | 3 | |
| Elective | 3 | |
| Credits | 6 | |
| 5th Semester/Term | ||
| Capstone | 3 | |
| Elective | 3 | |
| Credits | 6 | |
| Total Credits | 30 | |
Learning Outcomes
Upon successful completion of the program, graduates will:
- Integrate concepts and methodologies from diverse fields to address complex technological challenges, showcasing their ability to work effectively at the intersection of different disciplines.
- Develop the capacity to synthesize ideas from various domains, facilitating the creation of new knowledge in emerging technology areas, and demonstrate their ability to design and execute projects that contribute to the advancement of technology and its applications.
- Thrive in dynamic and ever-changing technology environments, while exhibiting a high degree of adaptability, enabling them to leverage their interdisciplinary education to capitalize on new opportunities within in-demand fields.
Policies
NYU Policies
University-wide policies can be found on the New York University Policy pages.
Tandon Policies
Additional academic policies can be found on the Tandon academic policy page.