Curriculum

The Master of Science in Engineering is a full-time STEM designated 30-point program. Students begin in the fall semester and may complete the program in May, August, or December of the following year.

Overview

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Foundation

Students take a series of seven core courses as a cohort, and enroll in elective courses in a concentration of their choice. The core courses cover the foundation needed to work in technical leadership and a survey of emerging technology problems.

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Sample Topics

Students choose a concentration from amongst graduate-level courses offered in the School of Engineering and Applied Science. Seven concentrations have been prepared, but students may customize their concentration in consultation with the Engineering Director of the program. Students may also add electives from other schools at Columbia. 

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Capstone

The Master of Science in Engineering culminates in a capstone project integrating the skills students developed in the core curriculum with the knowledge from their elective concentration. Students work in teams to develop a technical idea, a new product or new process. This may be the foundation for a start-up or the basis for future entrepreneurship or intrapreneurship. 

 

Core Courses (15 Points)

  1. ENGI E4501 Human-Centered Design and Innovation (1.5 points)
  2. ENGI E4502 Design of UI/UX for Connected Systems (3 points)
  3. ENGI E4503 Analytics in Python (0 points)
  4. ENGI E4504 Data, Models and Decisions (1.5 points)
  5. ENGI E4505 Frontiers of Tough Tech (3 points)
  6. ENGI E4507 Fundamental Design Tools (3 points)
  7. ENGI E4509 Strategy, Leadership and Organizational Change (3 points)

ENGI 4510 Capstone (3 points):

Applying core learning to a design or development challenge in the area of their elective Concentration.

 

Concentrations

Select nine credits from one concentration.

  • ELEN E4411: Fundamentals of Photonics (3 points)
  • ELEN E4944: Principles of Device Microfabrication (3 points)
  • ENME E4114: Mechanics of Fracture and Fatigue (3 points)
  • ENME E4115: Micromechanics of Composite Materials (3 points)
  • MECE E4212: Microelectromechanical Systems (3 points)
  • MSAE E4090: Nanotechnology (3 points)
  • MSAE E4102: Synthesis & Processing of Materials (3 points)
  • MSAE E4206: Electronic and Magnetic Properties of Solids (3 points)
  • MSAE E4215: Mechanical Properties of Structural Materials (3 points)
  • MSAE E4250: Ceramics & Composites (3 points)
  • MSAE E4260: Electrochemical Materials and Devices (3 points)
  • MSAE E4301: Materials Science Laboratory (3 points)
  • ELEN E4106: Advanced Solid State Devices & Materials (3 points)
  • ENME E4117: Mechanics of Fiber-Reinforced Composites (3 points)
  • CHEN E4620: Intro to Polymers (3 points)
  • CHEN E4630: Topics in Soft Materials (3 points)
  • CHEN E4665: Polymer Chemistry for Sustainable Solutions (3 points)
  • CHEN E4150: Computational Fluid Dynamics (3 points)
  • CHEN E4650: Polymer Physics (3 points)
  • COMS W4701: Artificial Intelligence (3 points)
  • COMS W4705: Natural Language Programming (3 points)
  • COMS W4731: Computer Vision I (3 points)
  • COMS W4732: Computer Vision II (3 points)
  • COMS W4773: Machine Learning Theory (3 points)
  • COMS W4774: Unsupervised Machine Learning (3 points)
  • COMS W4775: Causal Inference (3 points)
  • COMS W4776: Neural Networks and Deep Learning (3 points)
  • COMS W4995: Applied Deep Learning (3 points)
  • COMS W4995: Causal Inference for Data (3 points)
  • COMS W4995: Deep Learning for Computer Vision (3 points)
  • COMS W6706: Advanced Spoken Language Processing (3 points)
  • COMS E6998: Reinforcement Learning LLMs (3 points)
  • COMS E6998: Machine Learning Frontiers (3 points)
  • COMS E6998: High Performance Machine Learning (3 points)
  • COMS E6998: Deep Learning for Robot Manipulation (3 points)
  • EAEE E4000: Machine Learning for Earth and Environmental Engineering (3 points)
  • EAEE E4009: GIS-RES, Environment and Infrastructure Management (3 points)
  • ECBM E4040: Neural Networks and Deep Learning (3 points)
  • EEEL E4220: Energy System Economics (3 points)
  • ELEN E6908: Embedded AI (3 points)
  • IEOR E4523: Data Analytics (3 points)
  • MECE E4602: Introduction to Robotics (3 points)
  • MECS E4603: Applied Robotics (3 points)
  • MECE E4611: Robotics Studio (3 points)
  • MECE E6612: Robotics Studio (Advanced) (3 points)
  • MECE E6615: Advanced Robotic Manipulation (3 points)
  • MECE E6616: Robot Learning (3 points)
  • ORCS E4529: Reinforcement Learning (3 points)
  • ELEN E4720: Machine Learning for Signals, Information, and Data (3 points)
  • EECS E4764: Artificial Intelligence of Things (AIoT) (3 points)
  • MEEC E6600: Mathematics of Machine Learning, Signals and Control (3 points)
  • EECS E6694: GenAI and Modern Deep Learning (3 points)
  • EECS E6699: Mathematics of Deep Learning (3 points)
  • EECS E6720: Bayesian Models in ML (3 points)
  • ELEN E6820: Speech & Audio Processing & Recognition (3 points)
  • ELEN E6876: Sparse and Low-Dimensional Models for High (3 points)
  • ELEN E6885: Reinforcement Learning (3 points)
  • EECS E6892: Reinforcement Learning in Information Systems (3 points)
  • EECS E6893: Big Data Analytics (3 points)
  • EECS E6895: Advanced Big Data and Artificial Intelligence (3 points)
  • CSEE W4121: Computer Systems for Data Science (3 points)
  • EECS E4750: Heterogeneous Computing for Signal and Data Processing (3 points)
  • EECS E6891: Operating, Distributed and Runtime System Optimization through AI/ML Techniques (3 points)
  • CIEN E4253: Computational Solid Mechanics with AI (3 points)
  • CIEN E4256: Applied Machine Learning in Civil Engineering (3 points)
  • CHEN E4580: Artificial Intelligence in Chemical Engineering (3 points)
  • CHEN E4880: Atomistic Simulations for Science and Engineering (3 points)
  • CHEN E4180: Machine Learning Biological Applications (3 points)
  • EAEE E4000: ML for Env Eng Engineering (3 points)
  • CHEN E4231: Solar Fuels (3 points)
  • EAEE E4000: Machine Learning for Earth and Environmental Engineering (3 points)
  • EAEE E4002: Alternative Energy Resources (3 points)
  • EAEE E4100: A Better Planet by Design (3 points)
  • EAEE E4180: Electrochemical Energy Storage Systems (3 points)
  • EAEE E4300: Introduction to Carbon Management (3 points)
  • EESC W4008: Introduction to Atmospheric Science (3 points)
  • MECE E4211: Energy: Sources and Conversion (3 points)
  • MECE E4312: Solar Thermal Engineering (3 points)
  • ELEN E4361: Power Electronics (3 points)
  • ELEN E4511: Power Systems Analysis (3 points)
  • ELEN E4510: Renewable Energy and Smart Grid (3 points)
  • ELEN E6570: Future Energy: Economics, Systems, Policies (3 points)
  • ELEN E6905: Technologies, Market, Governance & Operations of Smart Grid (3 points)
  • COMS E6998: Machine Learning for Climate (3 points)
  • CIEN E4012: Sustainable Urban Systems (3 points)
  • CHEN E4201: Engineering Applications in Electrochemistry (3 points)
  • CHEN E4600: Aerosols (3 points)
  • CHEN E4860: NMR in Bio, Soft, and Energy Materials (3 points)
  • CHEN E4380: Green Chemistry (3 points)
  • CHEN E4331: Catalysis and Kinetics of CO2 Conversion (3 points)
  • CHEN E4665: Polymer Chemistry for Sustainable Solutions (3 points)
  • CHEN E4880: Atomistic Simulations for Science and Engineering (3 points)
  • EAEE E4200: Sustainable Mining (3 points)
  • EAEE E4220: Energy System Economics and Optimization (3 points)
  • EAEE E4300: Introduction to Carbon Management (3 points)
  • EAEE E4361: Economics of Mineral Extraction (3 points)
  • IEOR E4523: Data Analytics (3 points)
  • IEOR E4525: Machine Learning for FE & OR (3 points)
  • IEOR E4532: Data Visualization (3 points)
  • IEOR E4533: Performance, Objectives, and Results using Data (3 points)
  • IEOR E4534: Applied Analytics from Data to Decision (3 points)
  • IEOR E4576: Data-Driven Methods in Finance (3 points)
  • IEOR E4577: Applied Risk Analytics (3 points)
  • IEOR E4737: AI Applications in Finance (3 points)
  • IEOR E4742: Deep Learning for OR and FE (3 points)
  • BMEE E4740: Bioinstrumentation (3 points)
  • BMEN E4000: Life Science Future Entrepreneurs (3 points)
  • BMEN E4503: Drug and Gene Delivery (3 points)
  • BMEN E4590: Biomems: Cell and Molecular Applications (3 points)
  • BMEN E6000: Health as a System (3 points)
  • BMEN E6005: Biomedical Innovation I (3 points)
  • BMEN E6006: Biomedical Innovation II (3 points)
  • BMEN E6007: Lab-to-Market (3 points)
  • CHEN E4660: Biochemical Engineering (3 points)
  • CHEN E4700: Principles of Genomic Technologies (3 points)
  • CHEN E4870: Synthetic Organogenesis (3 points)
  • COMS W4731: Computer Vision (3 points)
  • COMS W4733: Computational Aspects of Robotics (3 points)
  • COMS W4771: Machine Learning (3 points)
  • MECE E4602: Robotics (3 points)
  • MECE E4611: Robotics Studio (3 points)
  • MECE E4613: Industrial Automation (3 points)
  • MECE E6616: Robot Learning (3 points)
  • MECE E6617: Advanced Kinematics, Dynamics and Control in Robotics (3 points)
  • MECS E6616: Robot Learning (3 points)
  • ELEN E4830: Digital Image Processing (3 points)
  • ELEN E6908: Embedded AI (3 points)
  • EECS E4764: Artificial Intelligence of Things (AIoT) (3 points)
  • MEEC E6600: Mathematics of Machine Learning, Signals and Control (3 points)
  • EEME E6911: Probabilistic Robotics (3 points)
  • MEEE E4600: Continuous Control Systems (3 points)
  • EEME E4601: Discrete Control Systems (3 points)
  • ELEN E4720: Machine Learning for Signals, Information and Data (3 points)
  • EECS E6992: Deep Learning on the Edge (3 points)
  • COMS W4731: Computer Vision I (3 points)
  • COMS W4732: Computer Vision II (3 points)
  • COMS E6998: Deep Learning for Robot Manipulation (3 points)
  • IEOR E4108: Supply Chain Analytics (3 points)
  • IEOR E4418: Transportation Analytics and Logistics (3 points)
  • IEOR E4505: OR in Public Policy (3 points)
  • IEOR E4507: Healthcare Operations Management (3 points)
  • IEOR E4601: Dynamic Pricing and Revenue Management (3 points)
  • EAEE E4200: Sustainable Mining (3 points)
  • EAEE E4220: Energy System Economics and Optimization (3 points)
  • EAEE E4361: Economics of Mineral Extraction (3 points)