cmu computer science courses
Students will prepare a written report and a poster presentation at the end of the semester to describe what they have accomplished. Prerequisites: (15-121 or 15-122) and (21-127 or 15-151). 16-385 Computer Vision Spring: 9 units Basic concepts in machine vision, including sensing and perception, 2D image analysis, pattern classification, physics-based vision, stereo and motion, and object recognition. To make the issues more concrete, the class includes several multi-week projects requiring significant design and implementation. 15-300 Research and Innovation in Computer Science Fall: 9 units This Fall course is the first part of a two-course sequence that is designed to help prepare students to invent the future state-of-the-art in the field of computer science. 15-424 Foundations of Cyber-Physical Systems Spring: 12 units Cyber-physical systems (CPSs) combine cyber effects (computation and/or communication) with physical effects (motion or other physical processes). Students in this course will understand the core principles behind CPSs, develop models and controls, identify safety specifications and critical properties of CPSs, understand abstraction and system architectures, learn how to design by invariant, reason rigorously about CPS models, verify CPS models of appropriate scale, understand the semantics of a CPS model and develop an intuition for operational effects. Students will learn strategies and techniques for finding information on the Web more efficiently; learn when to start with a search engine, a subject-oriented directory, or other tools; explore and practice using advanced search syntax for major search engines; experience specialized search engines for images, sound, multimedia, newsgroups, and discussion lists as well as subject-specific search engines; discover valuable resources to help keep you up-to-date in this fast-changing environment. Join Coursera for free and transform your career with degrees, certificates, Specializations, & MOOCs in data science, computer science, business, and dozens of … Corequisite: 21-127 or 15-151. 15-359 Probability and Computing Once every three semesters: 12 units Probability theory has become indispensable in computer science. This course is for students not in the computer science major or minor who are interested in advanced data structures. We begin with a brief introduction to computability and computational complexity. This course can be used to satisfy the Technical Communications requirement for the CS major. Prerequisite: 15-122 and 15-150. The course is designed to expose students to algorithms used for symbolic computation, as well as to the concepts from modern algebra which are applied to the development of these algorithms. Although students will learn the theoretical basis for such tools, the emphasis will be on actually using them on real examples. The course goes into more theoretical content on algorithm analysis than 15-122 and 15-150 while still including a significant programming component and covering a variety of practical applications such as problems in data analysis, graphics, text processing, and the computational sciences. (Laptops will be available for those without their own laptops.). In addition to the mathematical developments, we will discuss historical and philosophical aspects of the subject. Launched in 2018 by Kosbie and CMU colleague Mark Stehlik, Carnegie Mellon University’s Computer Science Academy (CMU CS Academy) is a rigorous online computer science program that has reached more than 5,600 teachers and mentors and 61,000 students around the world, giving a boost to schools that have limited opportunities to offer students courses in computer science and programming. Please note that many courses have prerequisites or corequisites, documented in CMU’s course catalog. These subjects are closely related to the application of mathematics in many areas, particularly computer science. We will cover many classical geometric constructions and novel algorithmic methods. After completing the course, students will be able to: *select and apply an appropriate supervised learning algorithm for classification problems (e.g., naive Bayes, perceptron, support vector machine, logistic regression). Introductory Computer Science Education at Carnegie Mellon University: A Deans' Perspective Randal E. Bryant Klaus Sutner Mark J. Stehlik August, 2010 CMU-CS-10-140 School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213 Abstract The School of Computer Science at Carnegie Mellon Universit y is planning major revisions to Personal computers have replaced studios full of sound recording and processing equipment, completing a revolution that began with recording and electronics. The problems will be submitted by other faculty who will grade the quality of the answers. Auditing: this course is usually full, and we generally receive many more requests to audit than we can accept. We will investigate questions about AI systems such as: how to represent knowledge, how to effectively generate appropriate sequences of actions and how to search among alternatives to find optimal or near-optimal solutions. Thesis prospectus is required and must be approved before student can start research. The CMU CS Academy curriculum includes four courses that leverage the expertise of CMU's top-ranked computer science school but are geared for use by a range of students, from those in middle school and afterschool programs to high school students. Throughout the course the computer algebra system Mathematica will be used for computation. Pittsburgh Campus Qatar Campus The M.S.-SE program does offer the possibility of taking courses in a variety of computing fields, including computer science, cyberphysical systems, mobile computing, security and privacy, data science, machine learning, and artificial intelligence, but its main orientation is software engineering. One major theme is the interplay between inductive types, which are built up incrementally; recursive functions, which compute over inductive types by decomposition; and proof by structural induction, which is used to prove the correctness and time complexity of a recursive function. NOTE: students must achieve a C or better in order to use this course to satisfy the pre-requisite for any subsequent Computer Science course. By developing a subtle pattern of reductions between classes we will suggest an (as yet unproven!) Course profiles are provided based on information developed by, and guidance from, individual course instructors. The course listings below are a representation of what this academic program requires. Prerequisites: 21-122 and (15-251 or 21-228). The School of Computer Science is regarded as one of the best places in the world to get a graduate degree in computer science.SCS offers a wide range of professional and academic Master's programs, a number of Ph.D. programs, and several interdisciplinary tracks. Designing algorithms to control CPSs, such as those in cars, aircraft and robots, is challenging due to their tight coupling with physical behavior. We will cover theory as well as practical application of ideas from Human-Computer Interaction. Computer science curriculum: free for all, designed for you. Second, for students to gain practical experience designing, implementing, and debugging real distributed systems. English (en) ... Search courses Go. 21-122 Integration and Approximation Fall and Spring: 10 units Integration by trigonometric substitution and partial fractions; arclength; improper integrals; Simpson's and Trapezoidal Rules for numerical integration; separable differential equations, Newton's method, Euler's method, Taylor's Theorem including a discussion of the remainder, sequences, series, power series. Topics include naming shared data, synchronizing threads, and the latency and bandwidth associated with communication. *recognize different types of unsupervised learning problems, and select and apply appropriate algorithms (e.g., clustering, linear and nonlinear dimensionality reduction). We will discuss UNIX, LaTeX, debugging and many other essential tools. 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