Cameras are now found everywhere, in our cell phones, automobiles, even in medical surgery tools. This course provides an introduction to fundamental concepts of distributed systems, and the design principles for building large scale computational systems. This course is designed to provide a comprehensive overview to computer graphics techniques in 3D modeling, image synthesis, and rendering. This course is to explore selected topics in data driven IoT/Edge Computing. Advanced Applied Mathematics. MATH 590. DMD We will study the theory of relational and XML data design; the basics of query languages; efficient storage of data, execution of queries and query optimization; transactions and updates; web-database development; and "big data" and NoSQL systems. Topics covered include architectural aspects of modern GPUs, with a special focus on their streaming parallel nature, writing programs on the GPU using high level languages like Cg and BrookGPU, and using the GPU for graphics and general purpose applications in the area of geometry modeling, physical simulation, scientific computing and games. As an Ivy League institution, and the first university in the nation, The University of Pennsylvania ensures its students a transformative experience. An important goal of the course is not simply to discuss issues and solutions, but to provide hands-on experience with a substantial implementation project. Course offered summer, fall and spring terms The purpose of this course is to present some of the advanced geometric methods used in geometric modeling, computer graphics, computer vision, etc. A plug-in to standard authoring tools such as Maya or Houdini must also be developed to enable importing of appropriate assets and/or exporting of results. - Lectures and exams presume knowledge of search and graph algorithms, and background in logic and probability. BMB 604. CIS 261 Discrete Probability, Stochastic Processes, and Statistical Inference. Background in computer graphics is requires (CIS 461 and 561). CIS 540 Principles of Embedded Computation. Students are expected to have a basic understanding of computer architecture and graphics, and should be proficient in OpenGL and C/C++. Reductions revisited, Cook-Levin Theorem, completeness, NL = co-NL. Prerequisite: In addition to course prerequisites, at least two additional undergraduate courses in math or theoretical CS. Post-Doctoral Fellow, University of Pennsylvania, Abramson Family Cancer Research Institute, Philadelphia, PA, 2011-2013. Students will have both written and practical, Python-based, assignments to build and deploy components of a blockchain solution, CIS 240 Introduction to Computer Systems. For Ph.D. candidates working exclusively on their dissertation research, having completed enrollment for a total of ten semesters (fall and spring). We will examine how XML standards enable information exchange; how web services support cross-platform interoperability (and what their limitations are); how to build high-performance application servers; how "cloud computing" services work; how to perform Akamai-like content distribution; and how to provide transaction support in distributed environments. In accordance with the requirements in the CIS Graduate Student Handbook, the following non-CIS courses** may be counted as electives toward the CIS/MSE & MCIT degrees: Please note that tuition/fees for courses taken outside SEAS may vary and be more.. BE 521 Brain Computer Interfacing Prerequisites: An advanced undergraduate course such as BIOL 421 or a graduate course in biology such as Biol 526 (Experimental Principles in Cell and Molecular Biology), BIOL 527 (Advanced Moleclar Genetics), BIOL 540 (Genetic Systems), or equivalent, is a prerequisite. It is recommended that students have some knowledge of logic, basic linguistics, and/or programming. The central theme is the view of programs and programming languages as mathematical objects for which precise claims may be made and proved. The first half of the course will involve fundamentals of mobile app development, where students learn about mobile app lifecycles, event-based programming, efficient resource management, and how to interact with the range of sensors available on modern mobile devices. How do you optimally encode a text file? This half-credit course provides a thorough introduction to Unix and Linux. Discrete Mathematics, Automata theory or Algorithms at the undergraduate level. The relevant principles underlying methods used for analysis in these areas will be introduced and discussed at a level appropriate for biologists without a background in computer science. That is, practical implementation of the algorithms is not taught but principles of the algorithms are covered using small sized examples. The Senior Thesis program is selective, and students are generally expected to have a GPA is in the top 10-20% to qualify. The goal of this course is to provide an opportunity for seniors to define, design, and execute a project of their own choosing that demonstrates the technical skills and abilities that they have acquired during their 4 years as undergraduates. Prerequisite: Students should have a good knowledge of object-oriented programming (C++) and basic familiarity with linear algebra and physics. The intended audience for this class is both those students who are CS majors as well as those intending to be CS majors. An introduction to the problems of computer vision and other forms of machine perception that can be solved using geometrical approaches rather than statistical methods. Enrollment is by permission of the instructor. Evaluation is based on regular homework assignments as well as a final project and class participation. This course assumes programming experience equivalent to CIS 110, CIS 120 or ESE 112. CIS 547 Software Analysis. This course focuses on the challenges encountered in building Internet and web systems: scalability, interoperability (of data and code), security and fault tolerance, consistency models, and location of resources, services, and data. Instead the trust is in the underlying cryptographic algorithms. This course will focus on research topics in computer architecture, and include reading and presenting research papers and an optional project. In addition to providing the student with a solid background in C#, this course also explores topics that the .NET platform exposes such as object oriented design, .NET runtime internals, and others based on class interest. Concepts used in designing circuits, processing signals on analog and digital devices, implementing computation on embedded systems, analyzing communication networks, and understanding complex systems will be discussed in lectures and illustrated in the laboratory. Unix, in its many forms, runs much of the world's computer infrastructure, from cable modems and cell phones to the giant clusters that power Google and Amazon. CIS 599 Independent Study for Masters Students. We will study techniques for locating machines, resources, and data (including directory systems, information retrieval indexing, ranking, and web search); and we will investigate how different architectures support scalability (and the issues they face). Topics covered will include traits and generics; memory safety (move semantics, borrowing, and lifetimes); Rust's rich macro system; closures; and concurrency. This semester's project will be a peer-to-peer implementation of a Googe-style search engine, including distributed, scalable crawling; indexing with ranking; and even PageRank. Home | We will explore the joys of function programming, using Haskell as a vehicle. Topics covered include: geometric coordinate systems and transformations; quaternions; parametric curves and surfaces; forward and inverse kinematics; dynamic systems and control; computer simulation; keyframe, motion capture and procedural animation; behavior-based animation and control; facial animation; smart characters and intelligent agents. CIS 518 Topics in Logic: Finite Model Theory and Descriptive Complexity. The course is not intended for computer science students who want to learn about biologically motivated algorithmic problems; BIOL 437/GCB 536 and GCB/CIS/BIOL537 are more appropriate. Topics will range from critical basic skills such as examin and editing files, compiling programs and writing shell scripts, to higher level topics such as the architecture of Unix and its programming model. CIS 497 - DMD Senior Project . Year 3: MATH 547. This class introduces aspiring data science technologists to the spectrum of ethical concerns, focusing on social norms like fairness, transparency and privacy. school of engineering and applied science. In this course, we'll explore how researchers and organizations like Microsoft, Google, and NASA are solving these hard problems, and we'll get to use some of the tools they've built! Object-oriented databases. An introduction to the intent, approach, and contribution of anthropology to the study of socialization and schooling in cross-cultural perspective. Senior standing or permission of instructor. This Freshman Seminar is designed to be a very introductory exposition about Quantum Computation and Quantum Information Science. This course consists of three parts: Basic of complexity - Big Oh, Sorting arrays, Searching, Recursion; Graph Algorithms - Shortest paths, Minimum Spanning Tree CIS 547 / CIS 573 Graduate Teaching Assistant University of Pennsylvania - Software Analysis & Testing. Can the artistic, aesthetic, and scientific realms be bridged to effectively promote and interpret the past? This class will focus on case studies, c and methods of how archaeology and the past are created, presented and used in movies, museums, games, the internet, and art. Prerequisite: Undergraduate-level knowledge of Operating Systems and Networking, programming experience. The Senior Capstone Project is required for all BAS degree students, in lieu of the senior design course. Freshmen standing. Introduction to Bioinformatics. You know how to write a "program". Course Overview. Ben Taskar, University of PennsylvaniaFollow. Concurrent distributed operation is emphasized. This course is appropriate as an upper-level undergraduate CIS elective. This course covers generations of wireless mobile network standards and systems, basic differences and their evolution, charting the development of mobile telecommunications systems from 3G, to today's state-of-the-art wireless technology 4G LTE, and the next generation wireless technology, 5G. This is an introductory course to Computer Vision and Computational Photography. Areas include DNA sequence alignment, genetic variation and analysis, motif discovery, study design for high-throughput sequencing RNA, and gene expression, single gene and whole-genome analysis, machine learning, and topics in systems biology. Nemirovsky Family Dean, Penn Engineering and Professor, Mechanical Engineering and Applied Mechanics (MEAM), Computer and Information Science (CIS), Electrical and Systems Engineering (ESE) Email: kumar@cis (.upenn.edu) Phone: 215-898-3630 Office: 470 Levine Building This course will introduce supervised learning (decision trees, logistic regression, support vector machines, Bayesian methods, neural networks and deep learning), unsupervised learning (clustering, dimensionality reduction), and reinforcement learning. As a side-effect of the material of this course you will learn about some aspects of large-scale software development assimilating large APIs. CIS 110 Introduction to Computer Programming. The technologies are spread across a number of engineering areas and each of them raise issues that are of current concern or are likely to be a future issue. Specifically: – Assignments involve programming in C++ using the LLVM compiler infrastructure. Also Offered As: GCB 535, MTR 535, PHRM 535, Prerequisite: BIOL 421 OR BIOL 526 OR BIOL 527 OR BIOL 528 OR BIOL 540, CIS 536 Fundamentals of Computational Biology, Introductory computational biology course designed for both biology students and computer science, engineering students. vector matrix math), curves and surfaces, dynamical systems (e.g. This course covers the theory and practice of software analysis -- a body of algorithms and techniques to reason about program behavior with applications to effectively test, debug, and secure large, complex codebases. The course then proceeds to consider various extensions of first-order logic including fixed-point operators, generalized quantifiers, infinitary languages, and higher-order languages. (If you got at least 4 in the AP Computer Science A or AB exam, you will do great.) The course covers a diverse set of fundamental building blocks from linguistics, machine learning, algorithms, data structures , and formal language theory, along with their application to a real and difficult problem in artificial intelligence.
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