Approved Non-CIS Electives

Approved Non-CIS Course Electives for CIS/MSE & MCIT Graduate Students:

In accordance with the requirements in the CIS Graduate Student Handbook, the following non-CIS courses** may be counted as electives toward the CIS/MSE & MCIT degrees: Please note that tuition/fees for courses taken outside SEAS may vary and be more.

Restrictions 1:

For the following courses listed below only one may be taken as an elective by CIS graduate students:

• EAS 500 Technical Communication in Engineering Practice
• EAS 510 Technical Communication & Academic Writing For Engineers
• EAS 512 Engineering Negotiation
• EAS 545 Engineering Entrepreneurship I
• EAS 546 Engineering Entrepreneurship II
• EAS 590 Commercializing Technology & EAS 591 Leading Technology Teams
• EAS 595 Foundations of Leadership
• IPD 515 Product Design
• IPD 529 Designing Connected Objects and Experiences
• IPD 572 Design Thinking & Making
• EDUC 677 Information & Community Technology for Education & Development
• NPLD 792 Social Entrepreneurship

Restrictions 2:

(Starting Fall 2021)

For the following courses listed below only one may be taken as an elective by CIS graduate students:

• BMIN 5220 AI III: Advanced Methods & Health Applications in Machine Learning
• FNCE 737 Data Science for Finance
• GAFL 531 Data Science for Public Policy
• GEOL 542 Data Analysis in Earth Science
• LARP 743 Geospatial Software Design
• STAT 777 Intro To Python Data Sci

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For the following courses listed below more than one course may be taken as an elective, except for courses that have a restriction: 

• BE 516 Introduction to High-Performance Scientific Computing
• BE 521 Brain Computer Interfacing
• BE 530/PHYS 585 Theoretical Neuroscience
• BE 567/GCB Modeling Biological Systems
• BMIN 5220 AI III: Advanced Methods & Health Applications in Machine Learning (Restriction 2)
• CRIM 502/602 Criminal Justice Analytics
• EAS 500 Technical Communication in Engineering Practice (Restriction 1)
• EAS 507 Intellectual Property & Business Law for Engineers
• EAS 510 Technical Communication & Academic Writing For Engineers (for non-native speakers of English) (Restriction 1)
• EAS 512 Engineering Negotiation (Restriction 1)
• EAS 545 Engineering Entrepreneurship I (Restriction 1)
• EAS 546 Engineering Entrepreneurship II (Restriction 1)
• EAS 590 Commercializing Software (Restriction 1)
• EAS 595 Foundations of Leadership (Restriction 1)
• ECON 681 Microeconomic Theory I
• ECON 682 Game Theory & Applications
• ECON 701 Microeconomic Theory
• ECON 703 Microeconomic Theory II
• ECON 713 Game Theory
• EDUC 542 Video Games & Virtual Worlds
• EDUC 545 Core Methods in Educational Data Mining
• EDUC 552 Video Games and Virtual Worlds as Sites for Learning
• EDUC 577 Selected Topics in Educational Linguistics – as topics vary seek explicit permission of program director for approval
• EDUC 677 Information & Community Technology for Education & Development (Restriction 1)
• ENM 502 Numerical Methods & Modeling
• ENM 503 Introduction to Probability & Statistics
• ENM 522 Numerical Methods for PDEs
• ENM 5310 Data-driven Modeling & Probabilistic Scientific Computing
• ENM 540 Topics in Computational Science & Engineering
• ESE 500 Linear System Theory
• ESE 504 Introduction to Optimization Theory
• ESE 505 Control of Systems
• ESE 5060 Introduction to Optimization Theory
• ESE 507 (TCOM 500) Introduction to Networks and Protocols
• ESE 5090 Quantum Circuits & Systems
• ESE 514 Graph Neural Networks
• ESE 516 IoT Edge Computing
• ESE 519 Real-Time and Embedded Systems
• ESE 520 Agent-Based Modeling & Simulation
• ESE 530 Elements of Probability Theory
• ESE 531 Digital Signal Processing
• ESE 532 System-on-a-Chip Architecture
• ESE 534 Computer Organization
• ESE 535 Electronic Design Automation
• ESE 539 Hardware/Software Co-Design for Machine Learning
• ESE 540 Engineering Economics
• ESE 542 Statistics for Data Science
• ESE 543 Human Systems Engineering
• ESE 546 Principles of Deep Learning
• ESE 544 Project Management
• ESE 545 Data Mining
• ESE 575 (TCOM 511) Into to Wireless Systems
• ESE 576 (TCOM 570) Digital Communication Systems
• ESE 590 Systems Methodology
• ESE 605 Modern Convex Optimization
• ESE 6150 F1/10 Autonomous Racing Cars
• ESE 618 Learning for Dynamics and Control
• ESE 650 Learning in Robotics
• ESE 6650 Datacenter Architecture
• ESE 674 Information Theory
• ESE 676 Coding Theory
• ESE 680 Dynamic Programming & Stochastic Control (special topic)
• ESE 680 Reinforcement Learning (special topic)
• FNAR 567 Computer Animation
• GAFL 531 Data Science for Public Policy (Restriction 2)
• GCB 536 Computational Biology
• IPD/OID 515 Product Design (Restriction 1)
• IPD 572 Design Thinking & Making (Restriction 1) 
• LAW 577 Internet Law
• LING 515 Dynamics of Language
• LING 525 Computer Analysis & Modeling of Biological Signals & Systems
• LING 545 Math Foundations of Language Communication  I
• LING 546 Math Foundations of Language Communication II
• LING 549 Mathematical Techniques in NLP
• MATH 500 Topology
• MATH 502 Abstract Algebra
• MATH 508 Advanced Analysis
• MATH 5010 Geometry-Topology, Differential Geometry
• MATH 513 Computational Linear Algebra
• MATH 514 Advanced Linear Algebra
• MATH 530 Mathematics of Finance
• MATH 546/STAT 530 Advanced Probability
• MATH 547/STAT 531 Stochastic Processes
• MATH 570 Introduction to Logic & Computability
• MATH 571 Introduction to Logic & Computability
• MATH 574 Mathematical Theory of Computation
• MATH 580 Combinatorial Analysis and Graph Theory
• MATH 581 Combinatorial Analysis and Graph Theory
• MATH 582 Applied Mathematics & Computation
• MATH 584 The Mathematics of Medical Imaging & Measurement
• MATH/BIOL 586 Topics in Mathematical Biology
• MATH 690 Mathematical Foundations of Program Semantics – Foundations of Computer Security
• MATH 691 Topics in Mathematical Foundations of Computer Security
• MEAM 5060 Failure Analysis of Engineering Materials
• MEAM 510 Design of Mechatronic Systems
• MEAM 520 Intro to Robotics
• MEAM 521 Introduction to Scientific Computing for Scientific Applications
• MEAM 620 Advanced Robotics
• MEAM 625 Haptic Interfaces for Virtual Environments & Teleoperation
• MEAM 646 Computational Mechanics
• MSE 561 Atomistic Modeling in Materials Science
• MSE 575 Statistical Mechanics
• MSE 5760 Machine Learning and Its Applications in Materials Science
• NPLD 792 Social Entrepreneurship (Restriction 1)

Course offerings/schedules for all departments can be found here.

Wharton Courses

The Wharton School of Business MUST approve your registration for the courses listed below. Click here for directions and the Wharton Authorization Request form.

• FNCE 611 Corporate Finance
• FNCE 717 Financial Derivatives
• FNCE 720 Investment Management
• FNCE/REAL 721 Real Estate Finance: Investment and Analysis
• FNCE 725 Fixed Income Securities
• FNCE 737 Data Science for Finance (Restriction 2)
• FNCE 738 Capital Markets
• FNCE 750 Venture Capitalism & Financial Innovation
• FNCE 892 Financial Engineering
• MKTG 712 Data Analysis for Marketing Decisions
• MKTG 776 Applied Probability Models in Marketing (as of fall 2020, this course will no longer count as a non-CIS elective)
• MKTG 777 Marketing Strategy & Technology (as of fall 2019, this course will no longer count as a non-CIS elective)
• MKTG 852 Marketing Analytics
• OIDD/IPD 515 Product Design
• OIDD 653 Mathematical Modeling & Its Application in Finance
• OIDD 654 Product Management
• OIDD 670 Simulation and Dynamic Competitive Strategy
• OIDD 950 Information Systems: Representation & Discovery
• OIDD 934 Dynamic Programming & Stochastic Models
• STAT 510 Probability
• STAT 500 Applied Regression & Analysis of Variance
• STAT 5030 Data Analytics and Statistical Computing
• STAT 511 Statistical Inference
• STAT 512/STAT 550 Mathematical Statistics
• STAT 515 Advanced Statistical Inference I
• STAT 520 Applied Econometrics I
• STAT 530 Advanced Probability
• STAT 531 Stochastic Processes
• STAT 533 Stochastic Processes
• STAT 553 Machine Learning
• STAT 542 Bayesian Methods & Computation
• STAT 571/STAT 701 Modern Data Mining
• STAT 705 Statistical Computing with R
• STAT 535/711 Forecasting Methods for Management
• STAT 770 Data Analytics & Statistical Computing
• STAT 722 Predictive Analytics
• STAT 776 Applied Probability Models in Marketing (as of fall 2019, this course will no longer count as a non-CIS elective)
• STAT 777 Intro To Python Data Sci (Restriction 2)
• STAT 900 Probability & Combinatorial Optimization
• STAT 9270 Bayesian Statistical Theory and Methods
• STAT 928 Statistical Learning Theory
• STAT 930 Probability Theory
• STAT 970 Mathematical Statistics
• STAT 974 Modern Regression
• STAT 991 Regularization Methods for Learning
• STAT 991 Topics in Modern Statistical Learning

**Courses not appearing on the above list but with strong technical and/or mathematical content may be counted toward the CIS MSE graduate degree with the prior approval of the CIS/MSE Program Chair.