This course provides a broad introduction to machine learning, datamining, and statistical pattern recognition. Topics include: (i) Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks). (ii) Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning). (iii) Best practices in machine learning (bias/variance theory; innovation process in machine learning and AI). The course will also draw from numerous case studies and applications, so that you'll also learn how to apply learning algorithms to building smart robots (perception, control), text understanding (web search, anti-spam), computer vision, medical informatics, audio, database mining, and other areas.

Fundamental concepts involved with basic robot technology concentrating on industrial robots (articulated serial manipulators). The material covered concentrates on robot mechanics, including geometric and kinematics analyses. Miscellaneous topics including vision systems, robot dynamics, and control are also be presented. The course has a project component dealing with programming of an industrial robot.

Introduction to the intellectual enterprises of computer science and the art of programming. This course teaches students how to think algorithmically and solve problems efficiently. Topics include abstraction, algorithms, encapsulation, data structures, databases, memory management, security, software development, virtualization, and websites. Languages include C, PHP, and JavaScript plus SQL, CSS, and HTML.

Capstone engineering design project; transition experience to the mechanical engineering profession in industry and graduate education.

Modeling, analysis, and synthesis of practical mechanical devices in which dynamic response is dominant consideration.

Background and nature of international political events.

Calculus-based probability and statistics: distribution theory, estimation, hypothesis testing, applications to engineering and the sciences.

Introduction to computer theory, programming and systems. Sets, functions, logic. Procedural programming in Java. Computer and data models.

Historical development of Western civilization from antiquity to the early modern era (c. 1600 C.E.)

Experimental methods in heat transfer, fluid flow, and thermodynamics.

Feedback and forward loop control design and simulation; discrete time and frequency domain methods with implementation considerations.

Capstone engineering design project; transition experience to the mechanical engineering profession in industry and graduate education.

Mechanical properties of metals, woods, and plastics; testing techniques and standards.

Design fundamentals, including design processes, project planning, creativity, manufacturing, and human factors.

Design of mechanical components to avoid failure during operation. Stress analysis, failure theories, and specific mechanical components in design context.

Transport and rate processes, conduction, convection, and radiation.

Studies of the Earth's lithosphere, hydrosphere, atmosphere, and biosphere systems and their interrelations with human dimensions.

Fundamentals of public speaking emphasizing content, organization, delivery, audience response.

Stresses and deformations in structural members and machine elements, combined stresses, stress transformation.

Instrumentation and measurement system analysis and design; sensors and actuators; computer data acquisition and control.

Analysis and synthesis of moving machinery.

Engineering details of viscous flow with losses, measurements, compressibility, turbomachinery, convective heat transfer.

Kinematics and kinetics of particles and rigid bodies; concepts of work-energy and impulse-momentum; computer applications; vector notation.

Basic analog and digital circuits and systems; introduction to electromechanical devices.

Output pricing and resources allocation; contemporary problems such as pollution, antitrust policy, and international trade.

Engineering design process with emphasis on teamwork, ideation, decision-making, project planning applied to a group design project.

First and second laws, property relationships, characteristic functions, thermodynamic solver, various thermodynamics applications.

Forces using vector notation; static equilibrium of rigid bodies; friction, virtual work, centroids, and moments of inertia.

Engineering drawings, materials, manufacturing, and safety. Hand tools, cutting, drilling, the lathe, mill and numerical control.

Engineering design process and the roles of visual communication with emphasis on 3D physical solid modelers and Pro/ENGINEER.

Characteristics of metallic, plastic, and ceramic material; basic principles which relate properties of materials to their atomic and microstructure.

Laboratory applications of principles covered in Engineering Materials

Fundamental aspects of chemistry and chemical principles; emphasis on structure, bonding, and stoichiometry.

Laboratory applications of principles covered in Chemistry I

Understanding and writing for rhetorical situations; critical reading and response; writing source-based argument for academic and public audiences.

First and second order equations, series, Laplace transforms, linear algebra, eigevalues, first order systems of equations, numerical techniques.

Programming and engineering problem solving techniques, algorithms and processes from physics and calculus first principles.

Vector functions, partial differentiation, cylindrical and spherical coordinates, multiple integrals, line integrals, Green's theorem.

The profession of mechanical engineering; history, educational process, ethics, licensing, problem solving, technology.

Survey of music from a wide range of periods and styles.

Electricity and magnetism, circuits, light, optics (calculus based).