Course Overview
This MITx course series covers advanced engineering topics including control systems, dynamics, and systems thinking.
It teaches learners to model, analyze, and optimize complex systems — applicable to manufacturing, robotics, smart kitchens, IoT devices, and process engineering.
The program provides a foundation in systems-level thinking for engineers and technical managers.
Learning Outcomes
Learners will be able to:
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Understand system dynamics and feedback loops
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Model continuous and discrete systems
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Design basic control systems for mechanical, electrical, or hybrid processes
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Apply systems thinking to optimize workflows and operational efficiency
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Analyze stability, response, and performance of dynamic systems
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Solve engineering problems using simulation and analytical methods
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Apply insights to manufacturing, robotics, and technology-enabled gastronomy systems
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Integrate cross-disciplinary engineering concepts in practical applications
Course Structure
| Module | Title | Description |
|---|---|---|
| 1 | Introduction to Systems Thinking | System components, interactions, feedback loops |
| 2 | Modeling Dynamic Systems | Differential equations, state-space representation |
| 3 | Control Theory Basics | Open-loop vs closed-loop, PID controllers, feedback principles |
| 4 | System Response & Stability | Transient vs steady-state response, eigenvalues, stability analysis |
| 5 | Mechanical & Electrical Dynamics | Mass-spring-damper systems, RLC circuits, analogies |
| 6 | Simulation Tools | MATLAB/Simulink or Python-based system modeling |
| 7 | Optimization & Trade-offs | System performance, constraints, multi-objective optimization |
| 8 | Case Studies in Engineering | Robotics, automation, process engineering examples |
| 9 | Applied Project | Model, simulate, and optimize a real-world system |
| 10 | Capstone Assignment | Systems-level design incorporating control, dynamics, and optimization |
Course Duration
| Mode | Duration |
|---|---|
| Self-paced | 8–10 weeks (8–10 hours/week) |
| Instructor-led | 6 weeks (10 hours/week) |
Assessment
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Weekly problem sets
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Simulation exercises
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Case study assignments
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Capstone project demonstrating systems integration
Included Materials
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Lecture videos by MIT faculty
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Simulation and modeling templates
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Example datasets for analysis
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Case study documents and reading materials
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System design guides
Prerequisites
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Calculus and linear algebra
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Introductory physics and engineering principles
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Basic programming recommended
Certification
MITx Verified Certificate — Engineering & Systems Thinking
Awarded upon completion of all modules and the capstone project.
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