Plans of Study – Data Sciences in London

UConn is partnering with AES for students to complete their MENG or Certificate in London. Read on for more information about the Engineering Data Sciences Program. 

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Select a Plan That Works for You

The London internship will occur in a sixth-month period over two semesters. The Engineering Data Sciences program must start in a fall semester. For questions on deviating from the following plans, please reach out to us at engrcaee@uconn.eduThere are two plans of study options for either the MENG or Certificate.

Your Plan of Study is determined by your catalog year. Please use your Advisement Report or Academic Requirements Report in StudentAdmin to determine your catalog year.


Four to six courses are offered every fall and spring semester in our online format that allows completion of the Master of Engineering degree quickly, from anywhere in the world. The internship abroad replaces the ENGR 5315 Capstone Project.*

MENG Core Courses (12 credits) 

  • ENGR 5311 – Professional Communication and Information Management 
  • ENGR 5312 – Engineering Project Planning and Management 
  • ENGR 5314 – Advanced Engineering Mathematics or 
  • CSE 5050 – Algorithms & Complexity or 
  • CSE 5500 Algorithms (choose 1) 
  • *ENGR 5315 – MENG Capstone Project – Students are encouraged to work on a company-sponsored project 

    Data Science Concentration Course (12 credits) 

    • CSE 5520 – Data Visualization and Communication 
    • CSE 5713 – Data Mining 
    • CSE 5717 – Big Data Analytics 
    • CSE 5819 – Introduction to Machine Learning  

    Technical Electives (6 credits total) 

    A minimum of two elective courses from the following list are required. Other CSE, ECE, ME, or SE courses may also be substituted if mutually agreed by the student, advisor, and the program director.  

    Advanced Systems Engineering 

    • SE 5702 – Data Science for Materials and Manufacturing 
    • CSE 5835/SE 5095 – Machine Learning for Physical Sciences & Systems 

    Computer Science & Engineering 

    • CSE 5050 Algorithms & Complexity (cannot be taken to earn credit after taking CSE 5500) 
    • CSE 5500 Algorithms 
    • CSE 5312 Architecture of Internet of Things 
    • CSE 5820 Machine Learning 
    • CSE 5850 Introduction to Cyber Security 

    Electrical and Computer Engineering 

    • ECE 6141 – Neural Networks for Classification and Optimization 
    • ECE 6437 – Computational Methods for Optimization 


    • ENGR 5314 - Advanced Engineering Mathematics 

    Mechanical Engineering 

    • ME 5511 – Principles of Optimum Design 
    • ME 5895 – AI for Design and Manufacturing 
    • (or when offered as): 
    • ME 5895 – Computational Nanomechanics 

    Certificate Plan

    The Graduate Certificate comprises 5 courses (15 credits) and can be completed in 1 to 2 years of part-time enrollment. Credits earned during a certificate can also be applied to a future MENG.

    The mandatory Industry Internship in London course (ENGR 5316) course covers the assessment and placement of your paid internship.

    Prerequisite requirements: Four semesters of Calculus: Calculus I, Calculus II, Calculus III, Linear Algebra, along with a programming course (this could be in C, C++, Java or Python) 

    Technical Core Course Choices (12 credits) 

    1. CSE 5717 – Big Data Analytics 
    2. CSE 5819 – Introduction to Machine Learning 
    3. CSE 5520 – Data Visualization and Communication 
    4. CSE 5713 – Data Mining