Machine Learning | NYU Tandon School of Engineering

Machine Learning

Learn the systems, tools, and logic behind machine learning and AI that influences our daily lives.


students working at laptops

Now Online:

Due to COVID-19, NYU has decided to continue to keep campus closed and move programs to an online platform. Machine Learning will be running remotely as an interactive online course for Spring and Summer 2021. NYU Housing will not be offered at this time. 

This is a great opportunity to take advantage of our STEM offerings from home and we encourage you to consider this special educational opportunity.


About

NYU Tandon's Spring Program for Machine Learning is a 4-month, 8-class online program that introduces high school students to the computer science, data analyses, mathematical techniques and logic that drive the fields of machine learning (ML) and artificial intelligence (AI). People are experiencing new and always improving applications of these fields every day: in video and image recognition technologies; interactive voice controls for homes; autonomous vehicles; real-time monitoring and traffic control; cutting-edge diagnostic medical technologies; and in ever more aspects of our daily lives.

student and teacher coding This program is overseen by faculty from the Electrical and Computer Engineering and Mechanical Engineering departments and their graduate students. It offers a unique opportunity to learn directly from some of today's most innovative researchers in the field.  Students will learn the core principles in machine learning such as model development through cross validation, linear regressions and neural networks. They will develop an understanding of how logic and mathematics are applied both to "teach" a computer to perform specific tasks on its own and to improve continuously at doing so along the way.

The program is suited for academically strong students who have an interest in computer and data science and the ways in which they are used in society to develop new capabilities, services and products. 


Syllabus & Curriculum

Students will learn the art and science of Machine Learning from the foundational mathematics to state-of-the-art models. This theory is brought to life by daily assignments and weekly projects that require programmatic implementation of machine learning algorithms. A strong emphasis is put on students learning the principles of engineering problem solving, and how these techniques can be used to tackle societal challenges. Students are exposed to higher levels of mathematics, computer and data-science, and electrical engineering in relation to machine learning. They complete the course with the confidence to explore these topics further and apply them to other areas of interest themselves.

classroom of students using laptops

Learning Outcomes

By the end of the program, students should have:

1. An understanding of the basic principles of AI and machine learning and how this can be used to tackle real world problems

2. Gained useful skills to formulate and solve machine learning problems 

3. Hands-on experience in programming to solve machine learning problems (data analysis, use of machine learning algorithms, analysis of results, etc


Spring

Instructors and students will expect to spend at least 5-6 hours every two weeks in face-to-face online instruction, and a few hours in weeks in between where instructors will mentor and help students with their projects. Instruction will be both synchronous, i.e. face-to-face via Zoom and other platforms, as well as asynchronous, i.e. time spent watching videos, playing videogames, and engaging with other content created for the course. In-class sessions will entail a mix of lectures, brainstorming and ideation exercises, and lab sessions where instructors will lead students through the specifics of code or art creation tools. There will also be sessions where students will share the content they’ve created, playtest their games with each other, and participate in online activities. 

 

Summer

Instructors and students will expect to spend at least 5 hours a day in online instruction. The program will consist of daily face-to-face meetings between instructors and students complemented with time spent working on the assignments, watching additional instructional videos, working with online content specifically developed for the program and engaging with other students through online weekly projects. Instruction will consist of online interactive lectures followed by practical sessions (e.g. problem formulation exercises, programming, weekly projects). We anticipate to conduct lectures twice a day, in the morning and afternoon, each lecture followed by practical assignments supervised by the instructors. There will also be sessions where students will share the results of their work and collaborate with each other to solve more complicated problems.



Who Can Apply?

  • High school students who have successfully completed Algebra 2 or equivalent and have had some programming experience in any language
  • Academically prepared, highly motivated students who are willing to take initiative and have achieved a minimum 3.0 GPA or equivalent
  • Applicants with a passion for science, technology, engineering, and math

*International students are welcome to apply but should be aware they are required to submit proof of English language proficiency. For more information, check our Informational Page.  


Program Details & Materials

Spring Sessions

Bi-weekly Saturdays 10:00am - 3:00pm with weekly 1 hour mentor check-ins on Tuesdays and Thursdays 6:00pm - 7:00pm

  • February 6, 2021 with mentor check-ins February 9 and 11, 2021
  • February 20, 2021 with mentor check-ins February 23 and 25, 2021
  • March 6, 2021 with mentor check-ins March 9 and 11, 2021
  • March 20, 2021 with mentor check-ins March 23 and 25, 2021
  • April 10, 2021 with mentor check-ins April 13 and 15, 2021
  • April 24, 2021 with mentor check-ins April 27 and 29, 2021
  • May 1, 2021 with mentor check-ins May 4 and 6, 2021
  • May 22, 2021 with mentor check-ins May 25 and 27, 2021

Summer Sessions

Choose one of the following sessions when you apply *

  • Session 1: June 21, 2021 - July 2, 2021 
  • Session 2: July 12, 2021 - July 23, 2021  
  • Session 3: August 2, 2021 - August 13, 2021

*Orientation for all sessions will be the Friday before beginning at 3pm.

Applications accepted on rolling basis, preferred May 25th deadline. 

Program Costs

  • Tuition: $2,000

Materials

Access to a computer and a good internet connection are the only requirements to participate in the program. All the material will be hosted online and easily accessible from a web browser and any additional software tool will be made freely available to the students.

students giving a presentation

Refund Policy

Tuition deposit is non-refundable. 

Questions? Check out our Tandon Spring and Summer Programs Informational Page, our FAQ below, or contact us at k12.stem@nyu.edu or 646.997.3524


FAQs

Program Questions

You must have some experience with a coding language in addition to completing Algebra 2 or equivalent. 


The GPA requirement is a minimum 3.0 or equivalent. 


Applications are accepted on a rolling basis.


Our programs are overseen by Tandon faculty, and we recruit current engineering and computer science students to serve alongside these experts as teachers and mentors.  Every classroom will have a minimum of one graduate student instructor, and at least one additional instructor will be assigned to each class of (maximum) 24 students.   


For additional information check out our helpful Tandon Spring and Summer Programs Informational Page.


Spring 2021 Application

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Summer 2021 Application (Opening end of January)