Quantitative Methods
in Systems Engineering

Course 4 of 4 that comprises the Architecture and Systems Engineering Professional Certificate Program. Learn the fundamentals of quantitative methods of systems engineering and the implementation process.

Start Date: July 10, 2017
End Date: August 6, 2017
Duration: 4 Weeks
Time Commitment: 4-5 hours per week
Learning Format: Online
CEU's: 2.0

Cost: $750 per course / $2,200 for entire program ($800 savings when you sign up for complete program)

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Future Run Date: February 19, 2018 - March 18, 2018


Organizations around the world strive to use quantitative information methods in their systems engineering practices, but many struggle to implement them effectively. This online course covers the fundamentals of quantitative methods in systems engineering and provides basic how-to instruction for implementing these methods. The course is designed for engineering practitioners and managers looking to increase the use of quantitative information methods in existing systems engineering practices.


This course is especially relevant for those in aerospace, automotive, and defense industries, and engineers at original equipment manufacturers (OEM). It’s also designed for systems engineering professionals, directors, and senior managers across a number of industries looking to innovate and optimize their operational, manufacturing, and design systems. Departmental teams are encouraged to apply here.


Learn the fundamentals of quantitative methods in systems engineering and determine when, where, and how to employ these methods and techniques. The curriculum provides learners with an overview of design space exploration using models, as well as methods for analyzing and presenting the output of a model. A number of tradespace models will be presented and exercised as case studies.

By the end of the course you will:

  • Define the criteria and decisions to be answered with quantitative analysis
  • Evaluate concept alternatives in order to recommend a preferred alternative
  • Structure a trade study
  • Identify the multiple key cost and benefit criteria that frame a system decision opportunity
  • Construct a value hierarchy for a stakeholder/beneficiary/decision-maker to inform system design decisions
  • Articulate the core concepts of value-based thinking
  • Choose the relevant axes and representations for a tradespace
  • Interpret the results of a tradespace
  • Identify the fuzzy Pareto front in a tradespace
  • Perform a sensitivity analysis
  • Critique a decision analysis model by identifying sources of uncertainty and variation

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Program Highlights

Video tutorials and research-based content from a host of MIT professors.

Guest lectures from industry experts from Boeing and NASA, US Air Force, General Electric, General Motors, Apple, MAN Truck and Bus AG.

Learn online - when and where you would like - as long as you complete each module by the assigned time.

Earn a Professional Certificate and CEUs from MIT.

Robust collaborative environment to network and connect with students.

Group projects based on real-world examples.

Meet the Instructors

Faculty Director of the Architecture and Systems Engineering: Models and Methods to Manage Complex Systems online program, Director of the System Architecture Lab, Massachusetts Institute of Technology

Bruce Cameron is the Director of the System Architecture Lab at MIT and a co-founder of Technology Strategy Partners (TSP), a boutique consulting firm. His research interests at MIT include technology strategy, system architecture, and the management of product platforms. Dr. Cameron has directed research projects for BP, Sikorsky, Nokia, Caterpillar, NSTAR, AMGEN, Verizon, NASA, and ESA. Prior to MIT, Dr. Cameron worked as an engagement manager at a management consultancy and as a system engineer at MDA Space Systems, and has built hardware currently in orbit. Dr. Cameron received his undergraduate degree from the University of Toronto and graduate degrees from MIT.

Director, Systems Engineering Advancement Research Initiative, Massachusetts Institute of Technology

Director Systems Engineering Advancement Research Initiative, MIT Principal Research Scientist, Sociotechnical Systems Research Center (SSRC)

Research Scientis, MIT Socio-technical Systems Research Center Co-Founder, MIT Systems Engineering Advancement Research Initiative (SEARI)