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Course Criteria
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0.00 Credits
A hands-on introducction to computer programming using Python with an emphasis on graphics and audio manipulations. No prior programming experience required. Not open to Computer Science majors.
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1.00 Credits
A brief introduction to the C programming language for students with a good working knowledge of Java and data structures. This course is good preparation for CMPSCI 230 and courses that use C and C++. Prerequisites: CMPSCI 187 or ECE 242 or permission of instructor. This course is for CMPSCI minors and majors only, but it does not count towards either degree.
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1.00 Credits
When performance and reliability are needed, more and more companies rely on Java. This 6 weeks course will leave students with a deeper knowledge of Java's strengths and weaknesses and a rough idea of what an industry experience might entail. Course topics will include a deep look into different features of Java, common interview questions, patching software, and code reviews. Prerequisites: CMPSCI 187. This course is for CMPSCI minors and majors only, but it does not count towards either degree.
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1.00 Credits
This course offers an introduction to working with Unix, and it is intended to help students work with tools commonly used in CS courses. The class is comprised of both discussion and hands-on exercises in the EdLab. Topics covered include working with the command line, installing and maintaining the OS and software packages, version control systems, compiling programs, and more. No previous experience with Unix is required. This course is for CS minors and majors only, but it does not count towards either degree.
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4.00 Credits
Development of individual skills necessary for designing, implementing, testing and modifying larger programs: use of various modern automated tools, design strategies and patterns, working with large code bases and libraries, code refactoring.
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4.00 Credits
Large-scale software systems like Google - deployed over a world-wide network of hundreds of thousands of computers - have become a part of our lives. These are systems success stories - they are reliable, available ("up" nearly all the time), handle an unbelievable amount of load from users around the world, yet provide virtually instantaneous results. On the other hand, many computer systems don't perform nearly as well as Google - hence the now-cliche "the system is down." In this class, we study the scientific principles behind the construction of high-performance, scalable systems. The course begins with a discussion of the relevant features of modern architectures, and moves up the stack from there to operating system services such as programming language runtime systems, concurrency and synchronization, with a focus on key operating system features, I/O and networking, and distributed services.
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4.00 Credits
Mathematical methods for dealing with uncertainty. Basic counting problems. Discrete probablitlity, expected value and variance. Random number generators and Monte Carlo simulation. Bayesian reasoning, naive Bayes classifiers. Markov processes. Programming projects.
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4.00 Credits
Lecture, discussion. Basic concepts of discrete mathematics useful to computer science: set theory, strings and formal languages, propositional and predicate calculus, relations and functions, basic number theory. Induction and recursion: interplay of inductive definition, inductive proof, and recursive algorithms. Graphs, trees, and search. Finite-state machines, regular languages, nondeterministic finite automata, Kleene's Theorem. Problem sets, 2-3 midterm exams, timed final.
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1.00 - 18.00 Credits
University of Massachusetts Amherst has not provided a description for this course
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3.00 Credits
Satisfies the Junior Year Writing requirement. The impact of computers on modern society. Prerequisites: CMPSCI major; ENGLWRIT 112 or equivalent.
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