Designing, Visualizing and Understanding Deep Neural Networks
Deep Networks have revolutionized computer vision, language technology, robotics and control. They have growing impact in many other areas of science and engineering. They do not however, follow a closed or compact set of theoretical principles.
Introduction to Machine Learning
Theoretical foundations, algorithms, methodologies, and applications for machine learning. Topics may include supervised methods for regression and classication
Introduction to Database Systems
Access methods and file systems to facilitate data access. Hierarchical, network, relational, and object-oriented data models, application generators, browsers, report writers, and transaction processing.
Intro to Computer Vision and Computational Photography
This advanced undergraduate course introduces students to computing with visual data (images and video). We will cover acquisition, representation, and manipulation of visual information from digital photographs, image analysis and visual understanding, and image synthesis
Introduction to General Astronomy
A description of modern astronomy with emphasis on the structure and evolution of stars, galaxies, and the Universe. Additional topics optionally discussed include quasars, pulsars, black holes, and extraterrestrial communication, etc. Individual instructor's synopses available from the department.
Introduction to Complex Analysis
Analytic functions of a complex variable. Cauchy's integral theorem, power series, Laurent series, singularities of analytic functions, the residue theorem with application to definite integrals. Some additional topics such as conformal mapping.
Numerical Analysis
Programming for numerical calculations, round-off error, approximation and interpolation, numerical quadrature, and solution of ordinary differential equations.
Efficient Algorithms and Intractable Problems
Introduction to the design and analysis of algorithms. Topics include asymptotic analysis, recurrence relations, divide-and-conquer algorithms, dynamic programming, greedy algorithms, data structures, graph algorithms, and randomized algorithms.
Foundations of Computer Graphics
Introduction to the fundamental concepts of computer graphics. Topics include graphics pipeline, 2D and 3D transformations, viewing, projections, rendering, texture mapping, ray tracing, graphics hardware, and animation.
Introduction to Abstract Algebra
An introduction to the basic concepts of abstract algebra, including groups, rings, and fields.
Great Ideas of Computer Architecture (Machine Structures)
Introduction to the fundamental concepts of computer systems through bare metal programming on the Raspberry Pi. Topics covered include assembly language, computer arithmetic, the hardware/software interface, and the basics of operating system design.
Computer Security
Introduction to computer security. Cryptography, authentication, access control, program security, malicious code, operating systems and network security, web security, privacy, and legal and ethical issues.
Introduction to Artificial Intelligence
Introduction to the ideas and techniques underlying the design of intelligent computer systems. Topics include search, game playing, knowledge representation, inference, planning, reasoning under uncertainty, machine learning, robotics, perception, and language understanding.
Introduction to Analysis
An introduction to the concepts and methods of real analysis, including the real number system, limits, continuity, differentiation, the Riemann integral, sequences, and series.
Linear Algebra
Matrices, vector spaces, linear transformations, inner products, determinants. Eigenvectors. QR factorization. Quadratic forms and Rayleigh's principle.Jordan canonical form, applications.Linear functionals.
Directed Group Studies for Advanced Undergraduates
Lead students in developing data science curriculum through DS modules program for other courses. Such curriculum includes data analysis, data visualization, and machine learning.
Accelerated Structure and Interpretation of Computer Programs
Implementing generic operations, streams, iterators, and techniques to support functional, object-oriented, and constraint-based programming in Scheme.
Multivariable Calculus
Parametric equations and polar coordinates. Vectors in 2- and 3-dimensional Euclidean spaces. Partial derivatives. Multiple integrals. Vector calculus. Theorems of Green, Gauss, and Stokes.
Linear Algebra and Differential Equations
Foundational linear algebra covering matrix operations, determinants, vector spaces, inner product spaces, eigenvalues, eigenvectors, orthogonality, symmetric matrices, linear second- order differential equations, first - order systems with constant coefficients, and Fourier series.
Music in American Culture
A survey of American music from the 17th century to the present, including art music, folk music, and popular music, and their effect on American culture.
Introduction to Logic
An introduction to the concepts and principles of logic, including formal and informal reasoning, logical analysis, and logical fallacies.
Data Structures
Introduction to data structures and their algorithms, including arrays, stacks, queues, linked lists, trees, binary search trees, balanced trees, graphs, and hash tables.
Calculus
Techniques of integration; applications of integration. Infinite sequences and series. First-order ordinary differential equations. Second-order ordinary differential equations; oscillation and damping; series solutions of ordinary differential equations.
Discrete Mathematics
A course on the study of logic, mathematical induction, sets, relations, functions, graphs, number theory, combinatorics, algebraic structures, and discrete probability theory.
Drugs and the Brain
Exploration of drugs' history, chemistry, effects on the brain, and botanical sources.