Systems Science and Engineering, BSE
Systems Engineers provide technical management for societal-scale problems that often encompass the connections between the physical and the information world. Examples of the many cutting-edge applications include autonomous robotics, smart buildings, national power grid management, global networks, service optimization, and biological systems. Systems engineering is the set of reusable mathematics, intellectual tools, and methodologies for attacking large-scale engineering problems. These common tools are adaptable for problems in different engineering domains (e.g., electrical, mechanical, biological, chemical, and computing) and help us understand, design, and manage systems that contain elements from multiple domains. Systems engineering deals with how we extract useful, abstract models from lower level systems, use these models to analyze and predict behavior, and use the analysis to control behavior and optimize/synthesize solutions. System engineering helps us understand what happens when we compose many elements, each with their own behavior, and how to design and constrain the individual elements to engineer desired behavior for the composed system.
For more information: https://www.seas.upenn.edu/prospective-students/undergrad/majors/systems-science-and-engineering/
Systems Science and Engineering (SSE) Major Requirements
37 course units are required.
| Code | Title | Course Units |
|---|---|---|
| Engineering | ||
| Systems Foundations | ||
| CIS 110 | Introduction to Computer Programming (or equivalent) | 1 |
| or ENGR 105 | Introduction to Scientific Computing | |
| ESE 111 | Atoms, Bits, Circuits and Systems 1 | 1 |
| CIS 120 | Programming Languages and Techniques I | 1 |
| ESE 204 | Decision Models | 1 |
| ESE 210 | Introduction to Dynamic Systems | 1 |
| ESE 224 | Signal and Information Processing | 1.5 |
| ESE 303 | Stochastic Systems Analysis and Simulation | 1 |
| Information Systems Electives | ||
| Select 3 from the following: | 3 | |
| Introduction to Computer Systems | ||
| Database and Information Systems | ||
| Foundations of Data Science | ||
| Introduction to Networks and Protocols | ||
| Agent-Based Modeling and Simulation | ||
| Intro to Linear, Nonlinear and Integer Optimization | ||
| Feedback Control Design and Analysis | ||
| Dynamical Systems for Engineering and Biological Applications | ||
| Estimation and Detection Theory | ||
| Data Mining: Learning from Massive Datasets | ||
| Scalable and Cloud Computing | ||
| Theory of Networks | ||
| Algorithmic Game Theory | ||
| Systems Design | ||
| Select one of the following: | 1 | |
| Software Design/Engineering | ||
| Embedded Software for Life-Critical Applications | ||
| Design of Smart Systems | ||
| Systems Methodology | ||
| Systems Project | ||
| Select one of the following: | 1 | |
| Introduction to Electrical and Systems Engineering Research Methodology | ||
| Embedded Systems/Microcontroller Laboratory | ||
| Control For Autonomous Robots | ||
| Feedback Control Design and Analysis 2 | ||
| Biomechatronics 2 | ||
| ESE 450 | Senior Design Project I - EE and SSE | 1 |
| ESE 451 | Senior Design Project II - EE and SSE | 1 |
| Engineering Elective | 1 | |
| Math and Natural Science | ||
| MATH 104 | Calculus, Part I | 1 |
| MATH 114 | Calculus, Part II | 1 |
| MATH 240 | Calculus, Part III | 1 |
| ESE 301 | Engineering Probability | 1 |
| ESE 402 | Statistics for Data Science | 1 |
| PHYS 140 | Principles of Physics I (without laboratory) | 1-1.5 |
| or PHYS 150 | Principles of Physics I: Mechanics and Wave Motion | |
| or PHYS 170 | Honors Physics I: Mechanics and Wave Motion | |
| or MEAM 110 | Introduction to Mechanics | |
| ESE 112 | Engineering Electromagnetics | 1.5 |
| or PHYS 141 | Principles of Physics II (without laboratory) | |
| or PHYS 151 | Principles of Physics II: Electromagnetism and Radiation | |
| or PHYS 171 | Honors Physics II: Electromagnetism and Radiation | |
| CHEM 101 | General Chemistry I | 1 |
| or EAS 091 | Chemistry Advanced Placement/International Baccalaureate Credit (Engineering Students Only) | |
| or BIOL 101 | Introduction to Biology A | |
| or BIOL 121 | Introduction to Biology - The Molecular Biology of Life | |
| MATH 312 | Linear Algebra | 1 |
| or MATH 314 | Advanced Linear Algebra | |
| or MATH 370 | Algebra | |
| Natural Science Lab (if applicable) 3 | .5 | |
| Professional Electives | ||
| Technology Management Electives | ||
| ESE 400 | Engineering Economics | 1 |
| or EAS 545 | Engineering Entrepreneurship I | |
| or EAS 595 | Foundations of Leadership | |
| or MGMT 235 | Technological Innovation and Entrepreneurship | |
| or MGMT 237 | Management of Technology | |
| or OIDD 236 | Scaling Operations in Technology Ventures: Linking Strategy and Execution | |
| Societal Problem Application | ||
| Select 3 Societal Problem Electives 4 | 3 | |
| General Electives 5 | ||
| EAS 203 | Engineering Ethics | 1 |
| Select 4 Social Science or Humanities courses | 4 | |
| Select 2 Social Science or Humanities or Technology in Business & Society courses | 2 | |
| Total Course Units | 37 | |
| 1 | If not taken by the end of freshman year, must be replaced by another department approved Engineering course. |
| 2 | If ESE 505 or BE 570 is taken, an additional .5 CU engineering credit is required |
| 3 | This category requires 10 CU, including two .5 CU Natural Science Labs. Several of the courses above are 1.5 CU and already include .5 CU Natural Science Lab. If the courses selected do not total 10 CUs, you will be required to complete the additional CUs required with up to two .5 CU Natural Science Labs from the following list: BIOL 124 Introductory Organismal Biology Lab, CHEM 053 General Chemistry Laboratory I, MEAM 147 Introduction to Mechanics Lab, PHYS 050 Physics Laboratory I, PHYS 051 Physics Laboratory II, or another department approved Natural Science Lab. |
| 4 | A complete list of approved SPA electives can be found on the ESE undergraduate programs webpage |
| 5 | Must include a Writing Seminar (a list of approved Writing Seminars can be found in the SEAS Undergraduate Handbook) |
Concentrations
Students may select one of three concentrations:
- Data Science and Artificial Intelligence
- Decision Science
- Robotics
The degree and major requirements displayed are intended as a guide for students entering in the Fall of 2020 and later. Students should consult with their academic program regarding final certifications and requirements for graduation.