Cognate Courses

AEROSP 315 - Aircraft and Spacecraft Structures

AEROSP 325 - Aerodynamics

Prerequisites: Math 216 and Aero 225
Credit: 4
Content: Fundamental concepts in aerodynamics. Students learn how airfoils produce lift and how the pressure distribution about an airfoil can be calculated. Introduces the boundary-layer concept, how boundary layers lead to drag, and what makes them prone to instability and turbulence or separation. Effects of the wing platform shape on lift and drag. Introduction to airfoil design, high-lift devices and high-speed aerodynamics.

AEROSP 335 - Aerospace Propulsion

Prerequisites: Aero 225 and Math 216
Credit: 4
Content: Air breathing propulsion, rocket propulsion, and an introduction to modern advanced propulsion concepts. Includes thermodynamic cycles as related to propulsion and the chemistry and thermodynamics of combustion. Students analyze turbojets, turbofans and other air-breathing propulsion systems. Introduces liquid- and solid-propellant rockets and advanced propulsion concepts such as Hall thrusters and pulsed plasma thrusters. Students also learn about the environmental impact of propulsion systems and work in teams to design a jet engine.

AEROSP 540 - Intermediate Dynamics

ASTRO 401 - Exoplanets

Enforced Prerequisites: MATH 215, 255 or 285, and prior or concurrent enrollment in PHYSICS 340 or PHYSICS 360, or graduate standing.
Credit: 3
Content: "Exoplanets" are planets found outside of our Solar System, orbiting stars other than the Sun. This course gives an overview of exoplanet science: the physics underlying topics within planet discovery and characterization; major and recent scientific results; and how these findings put our Solar System in context with and inform astrobiology.

ASTRO 402 - Stellar Astrophysics

Prerequisites: Math 216, and prior or concurrent enrollment in Physics 340
Credit: 3
Content: This course examines the appearance, structure, and evolution of stars. We examine the basic physical processes that cause stars to have their observed structures; a study of the energy generation through nucleosynthesis; the basic physical laws that lead to the structure of stars; the transfer of radiation through the outer parts of the star; how spectroscopic information informs us as to the composition and motion of stars; and an in-depth look at the late stages of stellar evolution and stellar death.

ASTRO 404 - Galaxies and the Universe

Prerequisites: Math 216 plus prior or current enrollment in Physics 340 and 390; or instructor’s permission.
Credit: 3
Content: Examines the properties of galaxies, large-scale structure in the universe, and cosmological models. Considers orbit theory, spiral arms, the missing mass in galaxies, galaxy evolution, and the starburst phenomenon. Examines the clustering of galaxies, the hot intra-cluster medium, and the dynamical evolution of clusters. Addresses leading astronomy topics, such as expansion of the universe, the cosmic microwave background, Big Bang nucleosynthesis, and the origin and growth of structure in the universe.

ASTRO 405 - High Energy Astrophysics

Prerequisites: Math 216, and prior or concurrent enrollment in Physics 340
Credit: 3
Content: Examines the accretion disk and jets of plasma around black holes and other compact objects. How stellar-mass black holes form the rapidly variable x-ray binary sources and how supermassive black holes at the centers of galaxies produce quasars. The explosions of massive stars supernovae and the possibly resulting neutron star or black hole. The origin of x-ray and gamma-ray background radiation fields, the origin of gamma-ray bursts, and the nature of cosmic rays.

ASTRO 406 - Computational Astrophysics

Prerequisites: Math 216, prior or concurrent enrollment in Physics 240 or 260, and some knowledge of programming.
Credit: 3
Content: Develops a practical working knowledge of the most widely used numerical methods in Astrophysics. Theory is put into practice by development and use of numerical routines some already written in the personal computer or workstation environment. Interpolation, curve fitting, root finding, quadrature, numerical integration of differential equations, and matrix solutions of sets of linear equations. Fourier methods. Numerical statistical analysis, with particular emphasis on the peculiarities and pitfalls associated with real Astronomical data.

BIOMEDE 331 - Introduction to Biofluid Mechanics

BIOMEDE 332 - Introduction to Biosolid Mechanics

Prerequisites: BIOMEDE 231, MATH 215 and MATH 216
Credit: 4
Content: This course covers the fundamentals of continuum mechanics and constitutive modeling relevant for biological tissues. Constitutive models covered include linear elasticity, nonlinear elasticity, viscoelasticity and poroelasticity. Structure-function relationships which link tissue morphology and physiology to tissue constitutive models will be covered for skeletal, cardiovascular, pulmonary, abdominal, skin, eye and nervous tissues.

BIOMEDE 424/MECHENG 424 - Engineering Acoustics

Prerequisites: MATH 216 and Physics 240
Credit: 3
Content: Vibrating systems; acoustic wave equation; plane and spherical waves in fluid media; reflection and transmission at interfaces; propagation in lossy media; radiation and reception of acoustic waves; pipes, cavities and waveguides; resonators and filters; noise; selected topics in physiological, environmental and architectural acoustics.

BIOMEDE 479 - Biotransport

BIOPHYS 370/PHYSICS 370/CHEM 370 - Physical and Chemical Principles Behind Biology and Medicine

BIOPHYS 417/PHYSICS 417/CHEM 417 - Dynamical Processes in Biophysics

Prerequisites: Math 216, and Physics 340 or Chem. 463
Credit: 3
Content: The physical basis of diffusive processes in biology and biochemistry, and optical spectroscopic means for measuring its rates. Topics include: membrane electrical potentials, nerve impulses, synaptic transmission, the physics of chemoreception by cells, motion and reaction kinetics of membrane components, optical microscopy, visible and UV light absorption, fluorescence and phosphorescence, quasielastic light scattering, mathematics of random fluctuations, and chaotic processes in biology.

BIOPHYS 535 - Biophysical Modeling

CHEM 370/BIOPHYS 370/PHYSICS 370 - Physical and Chemical Principles Behind Biology and Medicine

CHEM 417/BIOPHYS 417/PHYSICS 417 - Dynamical Processes in Biophysics

Prerequisites: Math 216, and Physics 340 or Chem. 463
Credit: 3
Content: The physical basis of diffusive processes in biology and biochemistry, and optical spectroscopic means for measuring its rates. Topics include: membrane electrical potentials, nerve impulses, synaptic transmission, the physics of chemoreception by cells, motion and reaction kinetics of membrane components, optical microscopy, visible and UV light absorption, fluorescence and phosphorescence, quasielastic light scattering, mathematics of random fluctuations, and chaotic processes in biology.

CHEM 453 - Biophysical Chemistry I: Thermodynamics and Kinetics

Prerequisites: CHEM 260 (or CHEM 261 and CHEM 330), CHEM 451, PHYSICS 240, and MATH 215 or CHEM 262
Credit: 3
Content: This course provides an introduction to quantum mechanics and its application to chemistry. It is the second of a 3-term sequence in physical chemistry and builds on material introduced in CHEM 260. The Schrodinger Equation is solved in one, two, and three dimensions for important chemical problems. Group theory and quantum chemistry are used to understand chemical bonding and advanced spectroscopy.

CHEM 461 - Quantum Mechanics

Prerequisites: ((CHEM 230 and CHEM 261) OR (CHEM 260, CHEM 370, BIOPHYS 370 or PHYSICS 370)) AND ((PHYSICS 235, 240, or 250) AND (MATH 215 or CHEM 262)). Should be elected concurrently with CHEM 462.
Credit: 3
Content: This course provides an introduction to quantum mechanics and its application to chemistry. Topics covered include:
The principles of classical physics.
The mathematical tools of quantum mechanics.
The postulates of quantum mechanics
Free particle and a particle in a box.
Approximate methods (the variational principle and time-independent perturbation theory).
Time-dependent perturbation theory and spectroscopy.
The harmonic oscillator and molecular vibrations.
Orbital angular momentum and molecular rotations.
The Hydrogen atom.
Spin angular momentum.
Multi-electron atoms (atomic orbitals).
The chemical bond in diatomic molecules (molecular orbitals).
Chemical bonding in polyatomic molecules

CHE 341 - Fluid Mechanics

Prerequisites: Preceded by Physics 140 and Math 215, preceded or accompanied by CHE 230 and Math 216
Credit: 4
Content: Fluid mechanics for chemical engineers. Mass, momentum, and energy balances on finite and differential systems. Laminar and turbulent flow in pipes, equipment, and porous media. Polymer processing and boundary layers. Potential, two-phase, and non-Newtonian flow.

CHE 342 - Mass and Heat Transfer

Prerequisite: CHE 230, CHE 341, and Math 216
Credit: 4
Content: Theories and applications of mass and heat transport phenomena. Fick's law. Steady and unsteady diffusion. Mass transfer coefficeients. Simultaneous momentum and mass transfer. Fourier's law. Steady and unsteady thermal conduction. Heat transfer coefficients. Heat exchangers. Condensation and boiling. Radiation. Kirchoff's law and view factors.

CHE 554/MATSCIE 554 - Computational Methods in MS&E and CHE`

CEE 450 - Introduction to Transportation Engineering

Prerequisite: MATH 215 and Physics 240 or graduate standing. Minimum grade of "C" required for enforced prerequisites.
Credit: 4
Content: Fundamentals of planning, design and operation of highway transportation facilities. Topics covered include driver and vehicle performance characteristics, highway geometric design principles, basics of traffic analysis, traffic signal operations, transportation planning, connected and automated vehicle technologies and their impacts to the transportation infrastructure.

CLIMATE 321/SPACE 321/EARTH 321 - Earth and Space Systems Dynamics

Prerequisites: CLIMATE/SPACE 320, MATH 215 and MATH 216
Credit: 3
Content: This course will describe the major wind systems and ocean currents that are important to climate studies. The primary equations will be developed and simple solutions derived that will explain many of these motions. The relations among the dynamics and other parameters in the climate system will be illustrated by examples from both paleo and present day systems.

CLIMATE 350/SPACE 350/EARTH 350 - Atmospheric Thermodynamics

Prerequisites: MATH 216 or equivalent. Minimum grade of "C" required for enforced prerequisite.
Credit: 3
Content: Fundamentals of thermodynamics are presented, including the First, Second and Third Laws, ideal gases, adiabatic processes, phase changes, vapor pressure, humidity and atmospheric stability. The Kinetic Theory of Gases provides a molecular perspective on the various forms of atmospheric water substance and on macroscopic phenomenology in general.

CLIMATE 380/SPACE 380/EARTH 381 - Introduction to Atmospheric Radiation

Prerequisites: MATH 216 or equivalent. Minimum grade of "C" required for enforced prerequisite.
Credit: 3
Content: Basic concepts and processes of radiative transfer including radiometric quantities, electromagnetic spectrum, absorption, emission and scattering. The physics laws governing these processes including the Planck Law and the Kirchhoff Law. Radiative properties of atmospheric constituents. Reflection and refraction. Introductory-level descriptions of relevant applications in atmospheric sciences and climate physics.

CLIMATE 401/EARTH 401 - Geophysical Fluid Dynamics

CLIMATE 411/EARTH 411 - Cloud and Precipitation Processes

CLIMATE 463/ENSCEN 463 - Air Pollution Meteorology

CLIMATE 479/ENSCEN 479 - Atmospheric Chemistry

CLIMATE 480/EAS 480 - Climate Change: A Multidisciplinary Approach to Problem Solving

Prerequisite: Senior or graduate standing, MATH 116
Credit: 3
Content: All sectors of society are affected by climate change: science, policy, business, economics, public health, energy, ecosystems, environmental engineering, journalism, religion, etc. This course explores the intersections of these communities and exposes students to the factual and contextual elements that will allow effective participation in the adaptation to climate change.

CMPLXSYS 425 - Evolution in Silico

Prerequisites: MATH 115; Comfort with Probability/Statistics; and Proficiency with Programming (e.g., CMPLXSYS 270 or MATH 463/BIOPHYS 463 or CMPLXSYS 391 or CMPLXSYS 530, etc.)
Credit: 3
Content: While every population of living organisms is evolving, not everything that evolves is alive. Nature's success at finding innovative solutions to complex problems has inspired many computational implementations of the evolutionary process. Some of the various implementations we will learn about with hands-on exercises include approaches for solving optimization problems, building controllers and/or bodies for robots, and using computational instances of Darwinian evolution to study fundamental questions in biology.

CMPLXSYS 530/ EPID 638 - Computer Modeline of Complex Systems

Prerequisites: CMPLXSYS 270 or some experience with computer programming and math modeling concepts.
Credit: 3
Content: Introduces students to basic concepts, tools , and issues which arise using computers to model complex systems. Emphasis is placed on the modeling process itself, from model design through implementation to analyzing, documenting, and communicating results. Case studies of computer models of complex systems, including adaptive and non-adaptive complex systems drawn from economics, ecology, immunology, epidemiology, evolutionary biology, political science, and cognitive science.

CMPLXSYS 535/ PHYSICS 508 - Theory of Social and Technological Networks

Prerequisites: Calculus and linear algebra; some computer programming experience recommended.
Credit: 3
Content: Introduce and develop the mathematical theory of networks, particularly social and technological networks; applications to important network-driven phenomena in the epidemiology of human infections and computer viruses, cascading failure in grids, network resilience, and opinion formation. Topics covered: experimental studies of social networks, WWW, internet, information, and biological networks.

DATASCI 406 - Computational Methods in Statistics and Data Science

Enforced Prerequisites: Linear Algebra (MATH 214 or 217 or 417) & Intro Programming (STATS 306 or DATASCI 306 or EECS 183 or EECS 280 or ENGR 101) & either (i) Intermediate Statistics (STATS 412 or STATS 426) or (ii) [Introductory Statistics (DATASCI 101 or STATS 206 or STATS 250 or STATS 280) & Probability (MATH/STATS 425 or 525)]
Credits: 3
Content: This course introduces basic computational methods as needed in statistics. It is aimed primarily at undergraduate majors in Statistics and Data Science.

DATASCI 415 - Data Mining and Statistical Learning

Enforced Prerequisites: Linear Algebra (MATH 214 or MATH 217 or MATH 417) and either (i) Intermediate Statistics (STATS 401 or STATS 412 or STATS 426) or (ii) [Introductory Statistics (DATASCI 101 or STATS 206 or STATS 250 or STATS 280) and Probability (MATH/STATS 425 or MATH/STATS 525)]
Credits: 4
Content: This course covers the principles of data mining, exploratory analysis, and visualization of complex data sets, and predictive modeling. The presentation balances statistical concepts (such as model bias and over-fitting data, and interpreting results) and computational issues (including algorithmic complexity and strategies for efficient implementation). Students are exposed to algorithms, computations, and hands-on data analysis in weekly discussion sessions.

DATASCI 451 - Bayesian Data Analysis

Enforced Prerequisites: Probability (STATS 412 or MATH/STATS 425 or MATH/STATS 525) and Computer Programming (STATS 306 or DATASCI 306 or EECS 280).
Credit: 4
Content: The course is an introduction to both the principles and practice of Bayesian inference for data analysis. At the end of this course students will be familiar with the Bayesian paradigm, and will be able to analyze different classes of statistical models. The course gives an introduction to the computational tools needed for Bayesian data analysis and develops statistical modeling skills through a hands-on data analysis approach. Topics include: prior/posterior distributions, Bayes rule, Markov Chain Monte Carlo computations, linear and generalized linear models, mixed effect models, hierarchical models, analysis of spatial data, model selection and comparison, model checking.

DATASCI 500/STAT 500 - Statistical Learning I: Regression

Prerequisite: Linear Algebra (at the level of MATH 214 or equivalent) AND Theoretical Statistics (at the level of STATS 426 or equivalent)
Credits: 3
Content: The course covers concepts and methods for regression analysis and applications. It covers both linear and generalized linear regression models. Topics for linear models include estimation, inference, interpretation of results, diagnostics, robust procedures, weighting and transformations, and model selection; more advanced techniques (such as splines, principal components analysis, and shrinkage estimators, including ridge regression and Lasso) will also be introduced. Topics for generalized linear models include logistic regression and Poisson regression. While there will be some theory, the emphasis will be on applications and data analysis.

EARTH 321/SPACE 321/CLIMATE 321 - Earth Systems Dynamics

Prerequisites: CLIMATE/SPACE 320, MATH 215 and MATH 216
Credit: 3
Content: This course will describe the major wind systems and ocean currents that are important to climate studies. The primary equations will be developed and simple solutions derived that will explain many of these motions. The relations among the dynamics and other parameters in the climate system will be illustrated by examples from both paleo and present day systems.

EARTH 350/CLIMATE 350/SPACE 350 - Atmospheric Thermodynamics

Prerequisites: MATH 216 or equivalent. Minimum grade of "C" required for enforced prerequisite.
Credit: 3
Content: Fundamentals of thermodynamics are presented, including the First, Second and Third Laws, ideal gases, adiabatic processes, phase changes, vapor pressure, humidity and atmospheric stability. The Kinetic Theory of Gases provides a molecular perspective on the various forms of atmospheric water substance and on macroscopic phenomenology in general.

EARTH/SPACE 370 - Solar-Terrestrial Relations

Prerequisite: MATH 216, Physics 240.
Credit: 4
Content: Introduction to solar terrestrial relations with an overview of solar radiation and its variability on all time-scales. The effects of this variability on the near-Earth space environment and upper atmosphere are considered, as well as effects on the lower and middle atmosphere with connections to weather and climate. Subjects are approached through extensive data analysis, including weekly computer lab sessions.

EARTH 381/CLIMATE 380/SPACE 380 - Introduction to Atmospheric Radiation

Prerequisites: MATH 216 or equivalent. Minimum grade of "C" required for enforced prerequisite.
Credit: 3
Content: Basic concepts and processes of radiative transfer including radiometric quantities, electromagnetic spectrum, absorption, emission and scattering. The physics laws governing these processes including the Planck Law and the Kirchhoff Law. Radiative properties of atmospheric constituents. Reflection and refraction. Introductory-level descriptions of relevant applications in atmospheric sciences and climate physics.

EARTH 401/CLIMATE 401 - Geophysical Fluid Dynamics

EARTH 483 - Geophysics Seismology

Prerequisites: Prior or concurrent election of Math 215 and Physics 240 or 260
Credit: 4
Content: Elastic properties of rocks, elastic waves, seismological instruments and data, use of body wave travel times, surface wave dispersion, and periods of free vibrations to infer the structure and composition of the earth's interior; earthquake intensity and magnitude scales; spatial, temporal, and magnitude distribution of earthquakes, earthquake source mechanisms, seismological contributions to understanding of earth dynamics and global tectonics, moonquakes, underground nuclear explosions and "man-made" earthquakes, and earthquake prediction and control.

EAS 480/CLIMATE 480 - Climate Change: A Multidisciplinary Approach to Problem Solving

Prerequisite: Senior or graduate standing, MATH 116
Credit: 3
Content: All sectors of society are affected by climate change: science, policy, business, economics, public health, energy, ecosystems, environmental engineering, journalism, religion, etc. This course explores the intersections of these communities and exposes students to the factual and contextual elements that will allow effective participation in the adaptation to climate change.

ECON 401 - Intermediate Microeconomic Theory

ECON 402 - Intermediate Macroeconomic Theory

Prerequisites: Econ. 101 and 102 and Math 115
Credit: 4
Content: This course in macroeconomics deals with the determination of broad economic aggregates such as national income, employment, the price level, and the balance of payments in both the short run and the long run. Rigorous analysis is used to understand the forces that determine these economic variables, and how they are affected by public policies.

ECON 409 - Game Theory

Prerequisites: Econ 401
Credit: 3
Content: Game theory is the study of strategic interactions, where economic agents ("players" in a "game") affect each other through their actions, and make their decisions in light of what others are likely to choose. Game theory provides a unified framework for addressing questions about cooperation, conflict, and coordination. By formalizing the situations that players face, we can trace the logical implications of our assumptions on players' preferences, beliefs, and methods of reasoning.

ECON 435 - Financial Economics

ECON 452 - Intermediate Introduction to Statistics and Econometrics II

Prerequisites: With a minimum grade of C-, ECON 451 or ECON 453, or STATS 426.
Credit: 4
Content: This course, a continuation of ECON 451, is intended to prepare students to conduct empirical research in economics. The classical linear regression model is developed with special emphasis on the basic assumptions of the model, economic situations in which the assumptions are violated, and alternative estimation procedures that are appropriate in these cases. Computer exercises are used to introduce students to special problems encountered in the analysis of economic data.

EECS Course Information

EECS 314 - Circuit Analysis and Electronics

Prerequisites: Math 216, Physics 240
Credit: 4
Content: A survey of electrical and electronic circuits for students not in EE or CE. Formulation of circuit equations; equivalent circuits; frequency response ideas; steady-state and transient response; introduction to amplifiers; operational amplifiers; survey of electronic devices and circuits. Use of computer simulations for analysis of more advanced circuits.

EECS 367 - Intro to Autonomous Robotics

Prerequisites: EECS 281 and (MATH 214 or 217 or 296 or 417 or 419 or ROB 101); (C or better; no OP/F). Enrollment in one minor elective allowed for Computer Science Minors.
Credit: 4
Content: A computational introduction to the modeling and control of autonomous robots and mobile manipulators. Programming projects and lectures cover 3D coordinate systems, axis-angle rotation, forward and inverse kinematics, physical simulation and numerical integration, motion control, path planning, high dimensional motion planning, and robot software systems. Emphasizes portable programming of general robots.

EECS 376/ ROB 380 - Foundations of Computer Science

EECS 428 - Intro to Quantum Nanotech

Prerequisites: PHYSICS 240, MATH 215, MATH 216
Credit: 3 (Non-LSA credit)
Content: This course introduces students to the emerging new field of quantum based nanotechnology. The course includes a range of topics such as the quantum vibrator, resonant tunneling, quantum circuits, a quantum flip flop, quantum information, quantum vacuum, and the role of quantum behavior in nano-devices and materials.

EECS 442 - Computer Vision

Enforced Prerequisites: [(EECS 281 and (MATH 214 or 217 or 296 or 417 or 419 or ROB 101)); (C or better, No OP/F)] or graduate standing.
Credit: 4
Content: This course is an introduction to 2D and 3D computer vision. topics include: cameras models, the geometry of multiple views; shape reconstruction methods from visual cues: stereo, shading, shadow, contours; low-level image processing methodologies such as edge detection, feature detection; mid-level vision techniques (segmentation and clustering); Basic high-level vision problems: face detection, object and scene recognition, object categorization, and human tracking.

EECS 445 - Introduction to Machine Learning

Prerequisites: EECS 281, completed with a minimum grade of C or better
Credit: 4
Content: Theory and implementation of state of the art machine learning algorithms for large-scale real-world applications. Topics include supervised learning (regression, classification, kernal methods, neural networks, and regularization) and unsupervised learning, (clustering, density estimation, and dimensionality and reduction).

EECS 448 - Applied ML for Modeling Human Behavior

Enforced Prerequisites: [(EECS 281 and (MATH 214 or 217 or 296 or 417 or 419 or ROB 101)); (C or better; No OP/F)] or Graduate Standing in CSE
Credit: 4
Content: Machine learning, with a focus on human behavior, across multiple modalities including speech and text. Teams complete projects based primarily on their individual interests centered on modeling an aspect of human behavior. Prior experience with speech/language or other data modeling is not needed.

EECS 453 - Principles of Machine Learning

Enforced Prerequisites: EECS 280 and (STATS 250 or 280 or 412 or 426 or EECS 301 or IOE 265 or TO 301) and (EECS 351 or MATH 214 or 217 or 296 or 417 or 419 or ROB 101); (C or better, No OP/F)
Credit: 4 (Non-LSA credit)
Content: Covers fundamental principles of machine learning, including unsupervised learning (e.g., clustering, mixture models, dimension reduction), supervised learning (e.g., regression, classification, neural networks and deep learning), and reinforcement learning. For each topic, mathematical principles, key algorithmic ideas, and basic theoretical insights will be highlighted.

EECS 465/ ROB 422 - Introduction to Algorithmic Robotics

Enforced Prerequisites: [EECS 280 and MATH 215; (C or better, No OP/F) and (Junior or Senior Standing)] or Graduate Standing
Credits: 3 (Non-LSA credit)
Content: An introduction to the algorithms that form the foundation of robot planning, state estimation, and control. Topics include optimization, motion planning, representations of uncertainty, Kalman and particle filters, and point cloud processing. Assignments focus on programming a robot to perform tasks in simulation.

EECS 475 - Introduction to Cryptography

Prerequisites: EECS 376; (C or better, No P/F) or Graduate Standing in CSE. Contact the EECS department for course availability as upper level courses are often restricted to declared CS majors or minors.
Credit: 4
Content: This course will study fundamental concepts, algorithms, encryption schemes, and protocols in cryptography. Main topics include: symmetric private key encryption, public key encryption, hash functions, digital signatures, and key distribution. The course emphasizes a rigorous mathematical study of the various cryptographic schemes and their security in terms of algorithmic complexity. A nontrivial part of the course will be devoted to algorithmic and mathematical background from number theory, algebra, and probability theory needed to gain a solid understanding of cryptography. Popular cryptographic schemes such as AES and RSA will be highlighted and their security will be rigorously investigated.

EECS 477 - Data Mining

Prerequisites: EECS 376; (C or better, No P/F) or Graduate Standing in CSE. Contact the EECS department for course availability as upper level courses are often restricted to declared CS majors or minors.
Credit: 4
Content: This course will study fundamental concepts, algorithms, encryption schemes, and protocols in cryptography. Main topics include: symmetric private key encryption, public key encryption, hash functions, digital signatures, and key distribution. The course emphasizes a rigorous mathematical study of the various cryptographic schemes and their security in terms of algorithmic complexity. A nontrivial part of the course will be devoted to algorithmic and mathematical background from number theory, algebra, and probability theory needed to gain a solid understanding of cryptography. Popular cryptographic schemes such as AES and RSA will be highlighted and their security will be rigorously investigated.

EECS 477—Introduction to Algorithms

Prerequisites: EECS 281 and EECS 376; (C or better, No OP/F).
Credit: 4
Content: Fundamental techniques for designing efficient algorithms and basic mathematical methods for analyzing their performance. Paradigms for algorithm design: divide-and-conquer, greedy methods, graph search techniques, dynamic programming. Design of efficient data structures and analysis of the running time and space requirements of algorithms in the worst and average cases.

EECS 550 - Information Theory

EECS 567 - Introduction to Robotics: Theory and Practice

Prerequisites: EECS 281
Credit: 3
Content: Introduction to robots considered as electro-mechanical computational systems performing work on the physical world. Data structures representing kinematics and dynamics of rigid body motions and forces and controllers for achieving them. Emphasis on building and programming real robotic systems and on representing the work they are to perform.

EECS 568 / ROB 530 / NAVARCH 568 - Mobile: Robotics: Methods and Algorithms

Prerequisites: Graduate standing or permission of instructor
Credits: 4 (Non-LSA credit)
Content: Theory and application of probabilistic techniques for autonomous mobile robotics. This course will present and critically examine contemporary algorithms for robot perception (using a variety of modalities), state estimation, mapping, and path planning. Topics include Bayesian filtering; stochastic representations of the environment; motion and sensor models for mobile robots; algorithms for mapping, localization, planning and control in the presense of uncertainty; application to autonomous marine, ground, and air vehicles.

EECS 572 - Randomness and Computation

EECS 586 - Design and Analysis of Algorithms

ENSCEN 463/CLIMATE 463 - Air Pollution Meteorology

ENSCEN 479/CLIMATE 479 Atmospheric Chemistry

EPID 633 - Introduction to Mathematical Modeling in Epidemiology and Public Health

EPID 638/ COMPLXSYS 530 - Computer Modeling of Complex Systems

Prerequisites: CMPLXSYS 270 or some experience with computer programming and math modeling concepts.
Credit: 3
Content: Introduces students to basic concepts, tools , and issues which arise using computers to model complex systems. Emphasis is placed on the modeling process itself, from model design through implementation to analyzing, documenting, and communicating results. Case studies of computer models of complex systems, including adaptive and non-adaptive complex systems drawn from economics, ecology, immunology, epidemiology, evolutionary biology, political science, and cognitive science.

IOE 310 - Introduction to Optimization Methods

IOE 465 - Design of Experiments

Prerequisites: IOE 366; C- or better or graduate standing
Credit: 3
Content: Linear models, Multi-colinarity and Robust Regression, Comparative Experiments, Randomized Blocks and Latin Squares, Factorial Designs, Confounding, Mixed Level Fractional Factorials, Random and Mixed Models, Nesting and Split Plots, Response Surface Methods, Taguchi Contributions to Experimental Design.

IOE 512 - Dynamic Programming

IOE 515 - Stochastic Processes

MATSCIE 330 - Thermodynamics of Materials

MATSCIE 554/CHE 554 - Computational Methods in MATSCIE and CHE

MECHENG 311 - Strength of Materials

MECHENG 336 - Thermodynamics II

MECHENG 360 - Modeling, Analysis and Control of Dynamic Systems

Prerequisites: ME 240
Credit: 4
Content: Unified approach to abstracting real mechanical, fluid, and electrical systems into proper models in graphical and state equation form to meet engineering design and control system objectives. Introduction to system analysis eigenvalues, time and frequency response and linear feedback control. Synthesis and analysis by analytical and computer methods.

MECHENG 424 - Engineering Acoustics

Prerequisites: Math 216 and EECS 230 or Physics 240
Credit: 3
Content: Vibrating systems; acoustic wave equation; plane and spherical waves in fluid media; reflection and transmission at interfaces; propagation in lossy media; radiation and reception of acoustic waves; pipes, cavities, and waveguides; resonators and filters; noise; selected topics in physiological, environmental and architectural acoustics.

MECHENG 440 - Intermediate Dynamics and Vibrations

MECHENG 540 - Intermediate Dynamics

MECHENG 567/EECS 567/MFG 567 - Robot Kinematics and Dynamics

NAVARCH 320 - Marine Hydrodynamics I

Prerequisites: ME 211 or ME 240 or permission
Credit: 4
Content: Concepts and basic equations of marine hydrodynamics. Similitude and dimensional analysis, basic equations in integral form, continuity, and Navier-Stokes equations. Ideal fluid flow, Euler's equations, Bernoulli equation, free surface boundary value problems. Laminar and turbulent flows in pipes and around bodies.

NAVARCH 565/ROB 535 - Self Driving Cars: Perception and Control

Prerequisite: Students are recommended to have a background in linear algebra & Differential equations. Programming skills in Python & MATLAB, Some C++
Credits: 3
Content: Self-driving cars are a transformative technology for society. This course covers the underlying technologies in perception and control. Topics include deep learning, computer vision, sensor fusion, localization, trajectory optimization, obstacle avoidance, vehicle dynamics. Course includes theoretical underpinnings of self-driving car algorithms and practical application of the material in hands-on labs.

NAVARCH 568 / EECS 568 / ROB 530 - Mobile Robotics: Methods and Algorithms

Prerequisites: Graduate standing or permission of instructor
Credits: 4 (Non-LSA credit)
Content: Theory and application of probabilistic techniques for autonomous mobile robotics. This course will present and critically examine contemporary algorithms for robot perception (using a variety of modalities), state estimation, mapping, and path planning. Topics include Bayesian filtering; stochastic representations of the environment; motion and sensor models for mobile robots; algorithms for mapping, localization, planning and control in the presense of uncertainty; application to autonomous marine, ground, and air vehicles.

NERS 311 - Elements of Nuclear Engineering and Radiological Sciences I

PHIL 414 - Mathematical Logic

PHYSICS 340 - Waves, Heat, and Light

PHYSICS 370/CHEM 370/BIOPHYS 370 - Physical and Chemical Principles Behind Biology and Medicine

PHYSICS 390 - Introduction to Modern Physics

PHYSICS 401 - Intermediate Mechanics

Prerequisites: Physics 126/128 or 240 or 260/241, and Math 216
Credit: 3
Content: Newtonian and Lagrangian mechanics: Kinematics and dynamics in one, two and three dimensions, vector analysis; motion under gravity, planetary motion; free and forced, damped and undamped harmonic oscillators; the conservation laws of mechanics; inertial and accelerated frames of reference, fictitious forces; rigid body mechanics; coupled oscillators.

PHYSICS 402 - Optics

Enforced Prerequisites: PHYSICS 340 or 360, and one of: MATH 216, 256, 286, 296 or 316: or graduate standing
Credit: 3
Content: The objective of this class is to give students a foundation in classical optics. Topics studied to cover the phenomena of physical optics, reflection, refraction, interference, diffraction, and polarization interpreted in terms of the wave theory of light. Selected topics in contemporary optics, such as fiber optics, lasers, and nonlinear optics will be covered.

PHYSICS 405 - Intermediate Electricity and Magnetism

Prerequisites: Physics 126/128 or 240 or 260/241, and Math 216
Credit: 3
Content: Emphasis is placed upon the basic physical principles including electrostatics, magnetostatics, time-dependent electromagnetic fields and the effect of fields on dielectric and magnetic media. An introduction to Maxwell's equations and electromagnetic radiation is included. Other topics may include AC circuits and superconductivity.

PHYSICS 406 - Statistical and Thermal Physics

Prerequisites: Physics 126/128 or 240 or 260/241, and Math 216
Credit: 3
Content: Introduction to thermal processes including the classical laws of thermodynamics and their statistical foundations: basic probability concepts; statistical description of systems of particles; thermal interaction; microscopic basis of macroscopic concepts such as temperature and entropy; the laws of thermodynamics; and the elementary kinetic theory of transport processes.

PHYSICS 417/CHEM 417/BIOPHYS 417 - Dynamical Processes in Biophysics

Prerequisites: Math 216, and Physics 340 or Chem. 463
Credit: 3
Content: The physical basis of diffusive processes in biology and biochemistry, and optical spectroscopic means for measuring its rates. Topics include: membrane electrical potentials, nerve impulses, synaptic transmission, the physics of chemoreception by cells, motion and reaction kinetics of membrane components, optical microscopy, visible and UV light absorption, fluorescence and phosphorescence, quasielastic light scattering, mathematics of random fluctuations, and chaotic processes in biology.

PHYSICS 508/CMPLXSYS 535 - Theory of Social and Technological Networks

Prerequisites: Calculus and linear algebra; some computer programming experience recommended.
Credit: 3
Content: Introduce and develop the mathematical theory of networks, particularly social and technological networks; applications to important network-driven phenomena in the epidemiology of human infections and computer viruses, cascading failure in grids, network resilience, and opinion formation. Topics covered: experimental studies of social networks, WWW, internet, information, and biological networks.

ROB 380/ EECS 376 - Foundations of Computer Science

ROB 422 / EECS 465 - Introduction to Algorithmic Robotics

Enforced Prerequisites: [EECS 280 and MATH 215; (C or better, No OP/F) and (Junior or Senior Standing)] or Graduate Standing
Credits: 3 (Non-LSA credit)
Content: An introduction to the algorithms that form the foundation of robot planning, state estimation, and control. Topics include optimization, motion planning, representations of uncertainty, Kalman and particle filters, and point cloud processing. Assignments focus on programming a robot to perform tasks in simulation.

ROB 530 / NAVARCH 568 / EECS 568 - Mobile: Robotics: Methods and Algorithms

Prerequisites: Graduate standing or permission of instructor
Credits: 4 (Non-LSA credit)
Content: Theory and application of probabilistic techniques for autonomous mobile robotics. This course will present and critically examine contemporary algorithms for robot perception (using a variety of modalities), state estimation, mapping, and path planning. Topics include Bayesian filtering; stochastic representations of the environment; motion and sensor models for mobile robots; algorithms for mapping, localization, planning and control in the presense of uncertainty; application to autonomous marine, ground, and air vehicles.

ROB 535/NAVARCH 565 - Self Driving Cars: Perception and Control

Prerequisite: Students are recommended to have a background in linear algebra & Differential equations. Programming skills in Python & MATLAB, Some C++
Credits: 3
Content: Self-driving cars are a transformative technology for society. This course covers the underlying technologies in perception and control. Topics include deep learning, computer vision, sensor fusion, localization, trajectory optimization, obstacle avoidance, vehicle dynamics. Course includes theoretical underpinnings of self-driving car algorithms and practical application of the material in hands-on labs.

SPACE 321/CLIMATE 321/EARTH 321 - Earth Systems Dynamics

Prerequisites: CLIMATE/SPACE 320, MATH 215 and MATH 216
Credit: 3
Content: This course will describe the major wind systems and ocean currents that are important to climate studies. The primary equations will be developed and simple solutions derived that will explain many of these motions. The relations among the dynamics and other parameters in the climate system will be illustrated by examples from both paleo and present day systems.

SPACE 350/EARTH 350/CLIMATE 350 - Atmospheric Thermodynamics

Prerequisites: MATH 216 or equivalent. Minimum grade of "C" required for enforced prerequisite.
Credit: 3
Content: Fundamentals of thermodynamics are presented, including the First, Second and Third Laws, ideal gases, adiabatic processes, phase changes, vapor pressure, humidity and atmospheric stability. The Kinetic Theory of Gases provides a molecular perspective on the various forms of atmospheric water substance and on macroscopic phenomenology in general.

SPACE 370/EARTH 370 - Solar Terrestrial Relations

Prerequisite: MATH 216, Physics 240.
Credit: 4
Content: Introduction to solar terrestrial relations with an overview of solar radiation and its variability on all time-scales. The effects of this variability on the near-Earth space environment and upper atmosphere are considered, as well as effects on the lower and middle atmosphere with connections to weather and climate. Subjects are approached through extensive data analysis, including weekly computer lab sessions.

SPACE 380/EARTH 381/CLIMATE 380 - Introduction to Atmospheric Radiation

Prerequisites: MATH 216 or equivalent. Minimum grade of "C" required for enforced prerequisite.
Credit: 3
Content: Basic concepts and processes of radiative transfer including radiometric quantities, electromagnetic spectrum, absorption, emission and scattering. The physics laws governing these processes including the Planck Law and the Kirchhoff Law. Radiative properties of atmospheric constituents. Reflection and refraction. Introductory-level descriptions of relevant applications in atmospheric sciences and climate physics.

SPACE 545 - High Energy Density Physics

Prerequisite: MATH 450, Physics 405 & Physics 406
Credit: 3
Content: Introduces students to fundamental tools and discoveries of high-energy density physics, where pressures are above a million atmospheres. Discusses fundamental physical models, equations of state, hydrodynamics including shocks and instabilities, radiation transport, radiation hydrodynamics, experimental technique, inertial fusion, experimental astrophysics and relativistic systems.

STATS 413 - Applied Regression Analysis

Enforced Prerequisites: Linear Algebra (MATH 214 or MATH 217 or MATH 417) and either (i) Intermediate Statistics (STATS 401 or STATS 412 or STATS 426) or (ii) [Introductory Statistics (DATASCI 101 or STATS 206 or STATS 250 or STATS 280) and Probability (MATH/STATS 425 or MATH/STATS 525)]
Credit: 4
Content: The following topics will be covered: a) models and methods of inference for simple and multiple regression, regression splines; b) dignostics, multicollinearity, influence, outliers, transformation, model selection, and dimension reduction; c) principal component regression, ridge and robust regression, non-linear regression, non-parametric regression and Lasso; d) generalized linear models, binary and Poisson regression.

STATS 415 - Data Mining and Statistical Learning

Enforced Prerequisites: Linear Algebra (MATH 214 or MATH 217 or MATH 417) and either (i) Intermediate Statistics (STATS 401 or STATS 412 or STATS 426) or (ii) [Introductory Statistics (DATASCI 101 or STATS 206 or STATS 250 or STATS 280) and Probability (MATH/STATS 425 or MATH/STATS 525)]
Credit: 4
Content: This course covers the principles of data mining, exploratory analysis and visualization of complex data sets, and predictive modeling, Topics include: a) techniques and algorithms for exploratory data analysis and for discovering associations, patterns, changes, and anomalies in large data sets; and b) modern methods for multivariate analysis and statistical learning in regression, classification, and clustering. The presentation balances statistical concepts (such as model bias and over-fitting data, and interpreting results) and computational issues (including algorithmic complexity and strategies for efficient implementation). Students are exposed to algorithms, computations, and hands-on data analysis in weekly discussion sessions.

STATS 426 - Introduction to Theoretical Statistics

Enforced Prerequisites: Linear Algebra (MATH 214 or MATH 217 or MATH 417) and Probability (MATH/STATS 425 or MATH/STATS 525 or STATS 412).
Credit: 3
Content: An introduction to theoretical statistics for students with a background in probability. Probability models for experimental and observational data, normal sampling theory, likelihood-based and Bayesian approaches to point estimation, confidence intervals, tests of hypotheses, and an introduction to regression and the analysis of variance.

STATS 500/DATASCI 500 - Statistical Learning I: Regression

Prerequisite: Linear Algebra (at the level of MATH 214 or equivalent) AND Theoretical Statistics (at the level of STATS 426 or equivalent)
Credits: 3
Content: The course covers concepts and methods for regression analysis and applications. It covers both linear and generalized linear regression models. Topics for linear models include estimation, inference, interpretation of results, diagnostics, robust procedures, weighting and transformations, and model selection; more advanced techniques (such as splines, principal components analysis, and shrinkage estimators including ridge regression and Lasso) will also be introduced. Topics for generalized linear models include logistic regression and Poisson regression. While there will be some theory, the emphasis will be on applications and data analysis.

STATS 510 - Probability and Stribution Theory

Prerequisite: MATH 215 (Calculus III) or equivalent
Credits: 3
Content: Essential concepts of probability and distribution theory that are important for statistical inference including: random variables, probability, conditional probability, distribution functions, independence, modeling dependence, transformations, quantiles, order statistics, laws of large numbers, central limit theorem, and sampling distributions.

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Aerospace Engineering

AEROSP 315 - Aircraft and Spacecraft Structures

AEROSP 325 - Aerodynamics

AEROSP 335 - Aerospace Propulsion

AEROSP 540 - Intermediate Dynamics

Astronomy

ASTRO 401 - Exoplanets

ASTRO 402 - Stellar Astrophysics

ASTRO 404 - Galaxies and the Universe

ASTRO 405 - High Energy Astrophysics

ASTRO 406 - Computational Astrophysics

Biomedical Engineering

BIOMEDE 331 - Introduction to Biofluid Mechanics

BIOMEDE 332 - Introduction to Biosolid Mechanics

BIOMEDE 424/MECHENG 424 - Engineering Acoustics

BIOMEDE 479 - Biotransport

Biophysics

BIOPHYS 370/PHYSICS 370/CHEM 370 - Physical and Chemical Principles Behind Biology and Medicine

BIOPHYS 417/PHYSICS 417/CHEM 417 - Dynamical Processes in Biophysics

BIOPHYS 535 - Biophysical Modeling

Chemistry

CHEM 370/BIOPHYS 370/PHYSICS 370 - Physical and Chemical Principles Behind Biology and Medicine

CHEM 417/BIOPHYS 417/PHYSICS 417 - Dynamical Processes in Biophysics

CHEM 453 - Biophysical Chemistry I: Thermodynamics and Kinetics

CHEM 461 - Quantum Mechanics

Chemical Engineering

CHE 341 - Fluid Mechanics

CHE 342 - Mass and Heat Transfer

CHE 554/MATSCIE 554 - Computational Methods in MS&E and CHE`

Civil and Environmental Engineering

CEE 450 - Introduction to Transportation Engineering

Climate and Space Sciences and Engineering

CLIMATE 321/SPACE 321/EARTH 321 - Earth and Space Systems Dynamics

CLIMATE 350/SPACE 350/EARTH 350 - Atmospheric Thermodynamics

CLIMATE 380/SPACE 380/EARTH 381 - Introduction to Atmospheric Radiation

CLIMATE 401/EARTH 401 - Geophysical Fluid Dynamics

CLIMATE 411/EARTH 411 - Cloud and Precipitation Processes

CLIMATE 463/ENSCEN 463 - Air Pollution Meteorology

CLIMATE 479/ENSCEN 479 - Atmospheric Chemistry

CLIMATE 480/EAS 480 - Climate Change: A Multidisciplinary Approach to Problem Solving

Complex Systems

CMPLXSYS 425 - Evolution in Silico

CMPLXSYS 530/ EPID 638 - Computer Modeline of Complex Systems

CMPLXSYS 535/ PHYSICS 508 - Theory of Social and Technological Networks

Data Science

DATASCI 406 - Computational Methods in Statistics and Data Science

DATASCI 415 - Data Mining and Statistical Learning

DATASCI 451 - Bayesian Data Analysis

DATASCI 500/STAT 500 - Statistical Learning I: Regression

Earth

EARTH 321/SPACE 321/CLIMATE 321 - Earth Systems Dynamics

EARTH 350/CLIMATE 350/SPACE 350 - Atmospheric Thermodynamics

EARTH/SPACE 370 - Solar-Terrestrial Relations

EARTH 381/CLIMATE 380/SPACE 380 - Introduction to Atmospheric Radiation

EARTH 401/CLIMATE 401 - Geophysical Fluid Dynamics

EARTH 483 - Geophysics Seismology

Environment and Sustainability

EAS 480/CLIMATE 480 - Climate Change: A Multidisciplinary Approach to Problem Solving

Economics

ECON 401 - Intermediate Microeconomic Theory

ECON 402 - Intermediate Macroeconomic Theory

ECON 409 - Game Theory

ECON 435 - Financial Economics

ECON 452 - Intermediate Introduction to Statistics and Econometrics II

Electrical Engineering & Computer Science

EECS Course Information

EECS 314 - Circuit Analysis and Electronics

EECS 367 - Intro to Autonomous Robotics

EECS 376/ ROB 380 - Foundations of Computer Science

EECS 428 - Intro to Quantum Nanotech

EECS 442 - Computer Vision

EECS 445 - Introduction to Machine Learning

EECS 448 - Applied ML for Modeling Human Behavior

EECS 453 - Principles of Machine Learning

EECS 465/ ROB 422 - Introduction to Algorithmic Robotics

EECS 475 - Introduction to Cryptography