Size and time scales. Historical astronomy. Astronomical instrumentation. Stars: spectra and classification. Stellar structure equations and survey of stellar evolution. Stellar oscillations. Degenerate and collapsed stars; radio pulsars. Interacting binary systems; accretion disks, x-ray sources. Gravitational lenses; dark matter. Interstellar medium: HII regions, supernova remnants, molecular clouds, dust; radiative transfer; Jeans' mass; star formation. High-energy astrophysics: Compton scattering, bremsstrahlung, synchrotron radiation, cosmic rays. Galactic stellar distributions and populations; Oort constants; Oort limit; and globular clusters.

This module contains a link to download the Canvas Course shell for this entire course. The link will allow instructors from institutions that use the Canvas LMS to download the entire Canvas course for use.

This module contains study guides for chapters 11-15 and 19-21 in the Concepts of Biology textbook. The study guides are a list of questions that Instructors can give to students to help them prepare for tests. They can also be used for homework or in-class assignments.

This module includes information about the course, information on how to obtain the textbook, a suggested course schedule, a course description and a list of learning outcomes.

This module contains lecture PowerPoint slides in pptx format for chapters 11-15 and 19-21 for the Concepts of Biology book by Rice University. These slides contain tables, illustrations and text and are suitable for use in face-to-face, hybrid and online classes. They contain extensive text and could be utilized as instructor notes as well. The Concepts of Biology book can be downloaded on the following website: https://openstax.org/.

This module contains lecture PowerPoint slides in pdf format for chapters 11-15 and 19-21 for the Concepts of Biology book by Rice University. They have been modified for ADA compliance for use with screen readers. These slides contain tables, illustrations and text and are suitable for use in face-to-face, hybrid and online classes. They contain extensive text and could be utilized as instructor notes as well. The Concepts of Biology book can be downloaded on the following website: https://openstax.org/.

This includes materials to be used for a General Biology II course (or Introduction to Biology II course) for non-science majors.

This course will look at the various mechanisms of evolution, how these mechanisms work, and how change is measured. The course will begin by reviewing the evolutionary concepts of selection and speciation. The student will then learn to measure evolutionary change and look at the history of life according to the fossil record and a discussion of the broad range of life forms as they are currently classified. Upon completion of this course, students will be able to: define evolution and describe different types of selection; provide examples of microevolutionary forces and describe how they impact the genetics of populations; describe the Hardy-Weinberg principle and solve problems related to Hardy-Weinberg equilibrium; provide examples of games used in evolutionary game theory; connect biological phenomena to game theory; develop simple phylogenies from molecular or morphological data; identify important evolutionary events that have occurred throughout geologic time; characterize and provide examples of major plant and animal phyla. (Biology 312)

This course focus on basic and advanced techniques on text-based information retrieval (IR), the study of the processing, indexing, querying, organizing, and classifying textual documents, including hypertext documents available on the world-wide-web.

This is a communication intensive supplement to Linear Algebra (18.06). The main emphasis is on the methods of creating rigorous and elegant proofs and presenting them clearly in writing.

How people make sense of their worlds symbolically through myth, ritual, metaphor, and cosmology. The structure of symbols, the natural and social elements they draw on, their social use, and the messages they convey. Students learn to record and analyze myth and ritual.

Fundamentals of characterizing and recognizing patterns and features of interest in numerical data. Basic tools and theory for signal understanding problems with applications to user modeling, affect recognition, speech recognition and understanding, computer vision, physiological analysis, and more. Decision theory, statistical classification, maximum likelihood and Bayesian estimation, non-parametric methods, unsupervised learning and clustering. Additional topics on machine and human learning from active research.

The applications of pattern recognition techniques to problems of machine vision is the main focus for this course. Topics covered include, an overview of problems of machine vision and pattern classification, image formation and processing, feature extraction from images, biological object recognition, bayesian decision theory, and clustering.

From satellites gathering imagery from hundreds of miles above the Earth's surface to aerial systems mounted with lasers capable of generating 3D maps with centimeter accuracy, we're gathering more data about our Earth from above than ever before. This course will help you make sense of these complex and exciting datasets. Whether your interest is in natural disasters, environmental assessment, or national security, we'll give you the tools, methods, and techniques to extract actionable and meaningful information from these data. This course will help you understand that an image is more than just a pretty picture.

This course focuses on the problem of supervised learning from the perspective of modern statistical learning theory starting with the theory of multivariate function approximation from sparse data. It develops basic tools such as Regularization including Support Vector Machines for regression and classification. It derives generalization bounds using both stability and VC theory. It also discusses topics such as boosting and feature selection and examines applications in several areas: Computer Vision, Computer Graphics, Text Classification and Bioinformatics. The final projects and hands-on applications and exercises are planned, paralleling the rapidly increasing practical uses of the techniques described in the subject.

The main aims of this seminar will be to go over the classification of surfaces (Enriques-Castelnuovo for characteristic zero, Bombieri-Mumford for characteristic p), while working out plenty of examples, and treating their geometry and arithmetic as far as possible.