Emerging Technologies Master's Degree | NYU Tandon | Digital Learning | NYU Tandon School of Engineering

Emerging Technologies, M.S.

Digital Learning at NYU Tandon
Online
Robot walking

Request More Information Apply FAQ

Build Your Own Master's Degree

In the Emerging Technologies Master of Science program at NYU Tandon, you will have the freedom to design a unique curriculum engineered by you to match your 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, you have the autonomy to select concentrations and courses from across several academic departments at Tandon. Optimize your studies by designing your own path, exploring the intersections across engineering disciplines that best fit your professional passions.

 

Program Director, Pete Voltz, provides an introduction to the Emerging Technologies Master's program.

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.

 

Curriculum Information

To complete the Emerging Technologies M.S. program, students are required to earn 30 total credits and fulfill the following requirements:

  • 3 Concentration Elective courses (9 credits)
  • 1 Concentration Capstone course (3 credits)
  • 18 credits of Emerging Technologies Electives

The 18 credits of elective courses may come from across academic departments at Tandon, including courses from the nine concentration areas: machine learning & AI, user experience & design, wireless & networking, cybersecurity, innovation & change management, robotics, data science, urban informatics, & software engineering. Students also are encouraged to explore courses from schools outside of Tandon. Prerequisites may be required to enroll in electives.

Program Requirements                Sample Plan of Study

Concentration Areas

Please note: These offerings can vary by semester and may be subject to change.

Required Course / Capstone:

CS-GY 6803
Information Systems Security Engineering and Management, 3 credits

Concentration Electives (students must take at least 9 credits from this list:

  • CS-GY 6813 Information, Security, and Privacy, 3 credits
  • CS-GY 6823 Network Security, 3 credits
  • CS-GY 9163 Application Security, 3 credits
  • CS-GY 6573 Penetration Testing & Vulnerability Analysis, 3 credits
  • CS-GY 9215 Special Topics: Cyber Risk Management, 1.5 credits
  • CS-GY 9215 Special Topics: Cyber Resiliency Management, 1.5 credits
  • CS-GY 9223 Special Topics: Offensive Security, 3 credits
  • CS-GY 9223 Special Topics: Mobile Security, 3 credits
  • MG-GY 8213 Information Security for Managers, 3 credits

Remaining 18 credits satisfied by electives from other concentrations or courses approved by advisor.

Required Course / Capstone:

CUSP-GX 7023 Applied Data Science, 3 credits

Concentration Electives (students must take at least 9 credits from this list):

  • BI-GY 7743 Machine Learning and Data Science for Bioinformatics, 3 credits
  • CS-GY 6053 Foundation of Data Science, 3 credits
  • CS-GY 6313 Information Visualization, 3 credits
  • CS-GY 6513 Big Data, 3 credits
  • CUSP-GX 7013 Intro to Applied Data Science, 3 credits
  • CUSP-GX 8093 Data Visualization, 3 credits
  • ECE-GY 6363 Data Center and Cloud Computing, 3 credits

Remaining 18 credits satisfied by electives from other concentrations or courses approved by advisor.

Required Course / Capstone:

MG-GY 9503 MOT Capstone Project Course

Concentration Electives (students must take at least 9 credits from this list):

  • MG-GY 6023 Economics & Strategy, 3 credits
  • MG-GY 7953 Global Innovation, 3 credits
  • MG-GY 8673 Technology Strategy, 3 credits

Remaining 18 credits satisfied by electives from other concentrations or courses approved by advisor.

Required Course / Capstone:

ECE-GY 7143 Advanced Machine Learning, 3 credits

OR

CS-GY 6943 Artificial Intelligence for Games, 3 credits

Concentration Electives (students must take at least 9 credits from this list):

  • ECE-GY 6143 Introduction to Machine Learning, 3 credits
  • CS-GY 6923 Machine Learning, 3 credits
  • CS-GY 6613 Artificial Intelligence I, 3 credits
  • CS-GY 6763 Algorithmic Machine Learning and Data Science, 3 credits
  • CS-GY 6643 Computer Vision, 3 credits
  • CS-GY 6953 Deep Learning, 3 credits
  • CS-GY 6033 Design & Analysis of Algorithms I, 3 credits
  • BI-GY 7743 Machine Learning and Data Science for Bioinformatics, 3 credits

Remaining 18 credits satisfied by electives from other concentrations or courses approved by advisor.

Required Course / Capstone:

ROB-GY 6323 Reinforcement Learning and Optimal Control for Robotics, 3 credits

OR

ROB-GY 6423 Interactive Medical Robotics, 3 credits

Concentration Electives (students must take at least 9 credits from this list):

  • ROB-GY 6003 Foundations of Robotics, 3 credits
  • ROB-GY 6203 Robot Perception, 3 credits
  • ROB-GY 6213 Robot Localization and Navigation, 3 credits
  • ROB-GY 6313 Robotic Gait and Manipulation, 3 credits
  • ECE-GY 6143 Introduction to Machine Learning, 3 credits
  • CS-GY 6923 Machine Learning, 3 credits
  • CS-GY 6763 Algorithmic Machine Learning & Data Science, 3 credits
  • CS-GY 6613 Artificial Intelligence I, 3 credits

Remaining 18 credits satisfied by electives from other concentrations or courses approved by advisor.

Required Course / Capstone:

CS-GY 6253 Distributed Operating Systems, 3 credits

Concentration Electives (students must take at least 9 credits from this list):

  • CS-GY 6063 Software Engineering I, 3 credits
  • CS-GY 6373 Programming Languages, 3 credits
  • CS-GY 6033 Design & Analysis of Algorithms I, 3 credits
  • CS-GY 9053 Special Topics: Intro to Java, 3 credits
  • CS-GY 9223 Special Topics: Open Source/Professional Software Development, 3 credits

Remaining 18 credits satisfied by electives from other concentrations or courses approved by advisor.

Required Course / Capstone:

CUSP-GX 7043 Civic Analytics and Urban Intelligence, 3 credits

Concentration Electives (students must take at least 9 credits from this list):

  • CUSP-GX 5053 Geographic Information Systems, 3 credits
  • CUSP-GX 6023 Introduction to Programming for Solving Urban Challenges, 3 credits
  • CUSP-GX 7013 Intro to Applied Data Science, 3 credits
  • CUSP-GX 7053 Innovative City Governance, 3 credits
  • CUSP-GX 8093 Data Visualization, 3 credits

Remaining 18 credits satisfied by electives from other concentrations or courses approved by advisor.

Required Course / Capstone:

DM-GY 9103 Special Topics: Project Design Studio, 3 credits

Concentration Electives (students must take at least 9 credits from this list):

  • DM-GY 6053 Ideation & Prototyping, 3 credits
  • DM-GY 6063 Creative Coding, 3 credits
  • DM-GY 6133 Mobile Augmented Reality Studio, 3 credits
  • DM-GY 7133 User Experience Design, 3 credits
  • DM-GY 9103 Special Topics: Visual Design Studio, 3 credits
  • CS-GY 6543 Human Computer Interaction, 3 credits

Remaining 18 credits satisfied by electives from other concentrations or courses approved by advisor.

Required Course / Capstone:

ECE-GY 7353 Network Modeling & Analysis, 3 credits

Concentration Electives (students must take at least 9 credits from this list):

  • ECE-GY 6013 Digital Communications, 3 credits
  • ECE-GY 6023 Wireless Communications, 3 credits
  • ECE-GY 6113 Digital Signal Processing I, 3 credits
  • CS-GY 6843 Computer Networking, 3 credits
  • ECE-GY 5373 Internet Architecture & Protocols, 3 credits
  • ECE-GY 6383 High Speed Networks, 3 credits

Remaining 18 credits satisfied by electives from other concentrations or courses approved by advisor.

Experiential Learning for Credit

At NYU Tandon experiential learning opportunities provide students the chance to engage in practical, hands-on learning to refine technical and leadership skills. The Emerging Technologies M.S. program allows for students to complete various opportunities for credit counting towards degree requirements. In adherence with NYU Tandon Graduate Academic policies, students may not complete more than a combined total of 9 credits of project, guided studies, readings, or thesis toward fulfillment of the MS degree requirements.

 

A Career in Tech, Engineered for You, Engineered by You

We are here to help!

Request More Information