The details of this course change from year to year, but its purpose is to cover theoretical topics related to programming languages. Prerequisite: CIS1200 This course covers the basics of a distributed ledger, how it is built, used, and secured. The focus of the course will be hands-on development of computer game development tools (e.g. Over the past few decades, randomization has emerged as a powerful resource in algorithm desgin. The specific topics will be announced (together with special prerequisites) each time offered. Prerequisite(s): CIS350 or CIS3501 or IMSE351 or (ECE370 and MATH276), CIS422 Massive Data Management 4 Credit Hours, An introduction to database systems, concepts, and techniques for big data. What are the limits of efficient computation? As a result of their game development efforts, students will learn first-hand about the creative process, design documentation, object-oriented software design and engineering, project management (including effective team collaboration and communication techniques), design iteration through user feedback and play-testing, and most importantly, what makes a game or virtual reality experience interesting and fun to play. While traditional image processing techniques will be discussed to provide context, the emphasis will be on cutting edge aspects of all areas of image analysis (including registration, segmentation, and high-dimensional statistical analysis). All ar welcome, including those with no programming experience. 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). The PDF will include all information unique to this page. A previous course in machine perception or knowledge of image processing, experience with an operating system and language such as Unix and C, and aptitude for mathematics. Designed specifically for students who are new to computer science, MCIT Online offers the same innovative curriculum and high-quality teaching as Penn's on-campus program. If you have never programmed before, you should take CIS1100 first. This course will focus on numerical algorithms and scientific computing techniques that are practical and efficient for a number of canonical science and engineering applications. They . The focus of this course will be on the development of analytics/data science applications. Build a strong foundation in computer science and gain real-world coding skills. (F,W,S). In particular, emphasis will be given to biological problem modeling and understanding the algorithms and mathematical procedures at the "pencil and paper" level. This course is focused on principles underlying design and analysis of computational elements that interact with the physical environment. A design project is required. This course introduces the theory and practice of formal methods for the design and analysis of concurrent and embedded systems. Students will take a deep dive into database management, design and computer programming languages. Computer vision technology has led to latest innovations in areas such as Hollywood movie production, medical diagnosis, biometrics, and digital library. Technical features to be designed and implemented include novel game mechanics and/or user interaction models, game physics, character animation, game AI (i.e. Prerequisite: CIS1200 or previous programming experience. This course will provide an introduction to programming in C++ and is intended for students who already have some exposure to programming in another language such as Java, C++ provides the programmer with a greater level of control over machine resources and are commonly used in situations where low level access or performance are important. Along the way, students will also pick up essential skills such as git, bash, HTML and CSS. At the end of the first semester, students must submit an intermediate report; if the supervisor and reader accept it, they can enroll in CIS4110. At the end of the second semester, students must describe their results in a written thesis and must present them publicly, either in a talk at Penn or in a presentation at a conference or workshop. CIS1400 Introduction to Cognitive Science. Through an interdisciplinary approach with a variety of methodologies, Information Science majors combine technical expertise in computer science with the social sciences to study how people and . The goals of this course are twofold: (1) to take good programmers and turn them into excellent ones, and (2) to introduce them to a range of modern software engineering practices, in particular those embodied in advanced functional programming languages. This course would focus on powerful general techniques for designing randomized algorithms as well as specific representative applications in various domains, including approximation algorithms, cryptography and number theory, data structure design, online algorithms, and parallel and distributed computation. Computer & Information Science Bachelor of Science in Artificial Intelligence Learn about the new Bachelor of Science degree in Artificial Intelligence with a concentration in Data and Computational Science Study with leaders in the field of computer science Review of regular and context-free languages and machine models. (F, W, S), Prerequisite(s): CIS1501 and MATH115 or MATH113 or Mathematics Placement with a score of 116, CIS205 Comp Programming for Engineers 3 Credit Hours. No credit for CIS majors. Prerequisite(s): (MATH115 or Mathematics Placement with a score of 116) and (CIS200 or IMSE 200) and CIS275, CIS316 Prac. Algorithms for planning and perception will be studied and implemented on actual robots. CIS3980 Quantum Computer and Information Science. Students will be expected to implement solutions and software tools using MATLAB/C++, practice state-of-the-art parallel computing paradigms, and learn scientific visualization techniques using modern software packages. (F,W,S), CIS4961 Design Seminar for SE I 2 Credit Hours, Software engineering students participate in the design and implementation of a major software project. CSCI-N 201 - Programming Concepts Credits: 3 Designed specifically for students without a background in computer science, the online Master of Computer and Information Technology (MCIT) degree program follows the same curriculum as Penn's highly regarded on-campus MCIT program. Prerequisite: Undergraduate-level knowledge of Operating Systems and Networking. This course covers techniques for retrieving ranked relevant documents from a text repository based on user queries, using various techniques for extracting and representing latent knowledge from these documents. CIS490I Advanced Topic: Deep Learning 3 Credit Hours. The BS involves a more substantial computing component and more of a science focus than the BA. We are looking for a variety of students from different majors and schools to bring their diverse skill sets to the course. 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. This course will be used for 'pilot versions' of new CIS courses of this type that the department is planning to offer. The BS CIS program is not accredited by any commission of ABET, Inc. (http://www.abet.org) and has not sought such accreditation. The computer science degree program provides students with a curriculum in the key domains of computer science. This course is intended to provide a hands-on experience with interesting things to do on images/videos. Finally , in part 3 we will discuss some related topics such as null hypothesis testing and the replication crisis. (F,S). complete the necessary prerequisite credits and after four semesters he earned enough credits to transfer into GWU's Computer Science program. Computer and Information Science Our Computer and Information Science Department is one of the largestand most up-to-datein New York. For example: OUTPUT "Welcome to BBC Bitesize Computer Science" Obtaining user input from a keyboard In our collaborative culture, you'll work with expert Penn faculty and classmates from all over the world. Upon completion of the course, this application will be deployed and made accessible to the public. CIS2610 Discrete Probability, Stochastic Processes, and Statistical Inference. This course focuses on the fundamentals of scaling computation to handle common data analytics tasks. Prerequisite: Previous expoure to majr concepts in linear algebra (i.e. 2nd order mass-spring-damper systems) and 3D computer graphics has also been assumed in the preparation of the course materials. Department Chairperson: Yedidyah Langsam Deputy Chairperson for Graduate . In addition to completion of the Dearborn Discovery Core, the following courses are required to earn a B.S. Readings or analytical assignments in accordance with the needs and interests of those enrolled and agreed upon by the student and an instructor, which shall not duplicate a formal course offering. The course will include other advanced topics, time permitting. Why does it make the errors that it does? Students may access their Degree Audit on-line at the University Registrar's site. Curriculum in Computer Science; Curriculum in Computer Science. Basic understanding of 3D graphics and animation principles, prior exposure to scripting and programming languages such as Python, C and C++, CIS5650 GPU Programming and Architecture. The School of Computing and Information Systems is an international research leader in computer science, information systems and software engineering. Student works with industrial sponsor in area of CIS. CIS4360 Introduction to Computational Biology & Biological Modeling. Concentration requirements are listed below. The structure of the course will be lecture-based using small-team based exercises for evaluation. This course is appropriate as an upper-level undergraduate CIS elective. Course Description: Introduction to Information Technology includes the foundation skills required for building computer systems. The course will require a significant term project in connected health or connected automotive domains. The Computer and Information Science master's degree program is designed to prepare students for professional practice, as well as further studies and research in the computing field. The BS CIS program offers students a broad, liberal education in the physical sciences, mathematics, and humanities, along with intensive study in computer science. The course balances theory with practice by "looking under the hood" of current animation systems and authoring tools and exams the technologies and techniques used from both a computer science and engineering perspective. This course is an introduction to deep learning, a branch of machine learning concerned with the development and application of modern deep neural networks. CIS2400 Introduction to Computer Systems. NOVA offered an impressive . CIS6010 Advanced Topics in Computer Architecture. This course investigates algorithms to implement resource-limited knowledge-based agents which sense and act in the world. The Computer Science curriculum is designed to offer students flexibility. The aim of the course will be to allo you to use Haskell to easily and conveniently write practical programs. The Bachelor of Science in Computer Information Systems program blends theory and practice to prepare its graduates for careers in fields such as software systems development, e-commerce, and network administration. Prerequisite(s): (CIS200 or ECE270) and (CIS310* or ECE370* or ECE372*), Restriction(s): Cannot enroll if Class is FreshmanCan enroll if Level is Undergraduate, CIS390 Topics in Computer Science 1 to 3 Credit Hours. The first of these results is used to show limitations on the expressive power of first-order logic over finite structures while the second result demonstrates that the problem of reasoning about finite structures using first-order logic is surprisingly complex. Interesting connections can be made between these logics because temporal and description logics are modal logics, which in turn can be seen, as can database constraint logics, as certain fragments of first-order logic. The hardware/systems requirement may be met by CIS4710/CIS5710; or CIT5930 and CIT5950; or CIS2400 (with CIS4710/CIS5710 recommended); or equivalent coursework. This course provides a foundation for further studies in computer and information science and emphasizes a structured approach to problem solving and algorithm development. Four additional science credits; must be a different subject than the two course sequence prerequisite: Select 24 credit hours from the following: Any 100 to 400 level course with no more than 6 credits, as needed to get a minimum of 120 credits for graduation. In part 1 of the course we will examine how, in practice, researchers invoke at least three logically and conceptually distinct meanings of "explanation:" identification of causal mechanisms; ability to predict (account for variance in) some outcome; and ability to make subjective sense of something. This course will introduce the fundamental concepts and algorithms that enable computers to learn from experience, with an emphasis on their practical application to real problems. The graphics processing unit (GPU) has grown in power over recent years, to the point where many computations can be performed faster on the GPU than on a traditional CPU. A candidate for the degree of BS in CIS is required to select one of three concentrations: Computer Science, Information Systems, or Game Design. This class introduces aspiring data science technologists to the spectrum of ethical concerns, focusing on social norms like fairness, transparency and privacy. The duration of the project is two semesters. Main content. Continuation of CIS4000. Your tasks will include planning, analyzing, designing, constructing, and maintaining these areas. The purpose of this course is to deconstruct the hype by teaching deep learning theories, models, skills, and applications that are useful for applications. The course introduces students in engineering and computer science to fundamentals of robotics technology, programming and their applications in industrial environment. Prerequisite(s): CIS350 or CIS3501 or IMSE350 or (ECE370 and MATH276) or (ECE370 and ECE276), CIS481 Computational Learning 3 Credit Hours, This course covers basic computational aspects of learning to perform a task and improve with experience. Is information on your PC safe and should law enforcement be able to access information you enter on the Web? The first phase introduces the concepts of modern computer science, including structured programming languages and efficient, productive programming. The course will also provide insight into many open research problems in this area. This course will teach the fundamentals of developing web applications using Ruby on Rails, a rapid-development web framework developed by Basecamp, and adopted by companies like Airbnb, GitHub, Bloomberg, CrunchBase, and Shopify. Topics include MapReduce, similarity search, mining real-time data streams, link analysis, clustering, recommender systems, social network graph mining, and large scale data mining tasks. (YR), Prerequisite(s): (CIS200 or CIS2001) and MATH396, CIS447 Intro Computr & Ntwrk Security 3 Credit Hours. This course will be comprised of one lecture hour and one two-hour laboratory. This project-oriented course is centered around application development on current mobile platforms like iOS and Android. This half-credit course provides a thorough introduction to Unix and Linux. In this degree program, you will learn about the theory, experimentation, and engineering that form the basis for the design and use of computers. Prerequisite(s): (CIS350 or CIS3501 or IMSE350) or (ECE370 and (ECE276 or MATH276)), CIS446 Wireless & Mobi Comp Security 3 Credit Hours, Full course title: Wireless and Mobile Computing Security. movement control, path planning, decision making, etc. For specific topic, consult current semester's Schedule of Classes. The Bachelor of Science in Information Science (InfoSci) 4-year degree program at College Park teaches students skills in technical areas such as database design, information architecture, web/mobile development, data analytics, and cybersecurity alongside areas of the social sciences, leadership, and the humanities - addressing the growing and unique need for information professionals who . The goal of this course is to provide an opportunity for seniors to define, desand execute a project of your own choosing that demonstrates the technical skiland abilities that you have acquired during your 4 years as undergraduates. A significant discussion of algorithm complexity theory, including time and space trade-offs and elementary computability theory, is included. Function effectively as a member or leader of a team engaged in activities appropriate to the programs discipline. Process management, CPU scheduling, memory management, file systems and I/O devices. This course covers a variety of advanced topics in machine learning, such as the following: statistical learning theory (statistical consistency properties of surrogate loss minimizing algorithms); approximate inference in probabilistic graphical models (variational inference methods and sampling-based inference methods); structured prediction (algorithms and theory for supervised learning problems involving complex/structured labels); and online learning in complex/structured domains. Particular topics include operational techniques for formal definition of language features, type systems and type safety properties, polymorphism, constructive logic, and the Coq proof assistant. A survey of computer science topics, including history of computing, office productivity software, the internet, HTML, JavaScript, web design, algorithms, assemblers and compilers, gates and logic design, models of computation, artificial intelligence and expert systems, computing ethics, privacy issues, intellectual property. After a brief introduction to the language, programming assignments will be in Python. Course covers Java Programming language, focusing on GUI development, distributed computing and network applications. This course is to explore selected topics in data driven IoT/Edge Computing. The course balances theory with practice by "looking under the hood" of current animation systems and authoring tools and exams the technologies and techniques used from both a computer science and engineering perspective. We will aim to cover practical issues such as programming and the use of programs, as well as theoretical issues such as algorithm design, statistical data analysis, theory of algorithms and statistics. The course projects require knowledge of C/C++. The course requires a degree of mathematical sophistication. Topics include learning frameworks and problem formulations; standard models, methods, computational tools, algorithms and modern techniques; and methodologies to evaluate learning ability and to automatically select optimal models. Both degree programs are offered through the Department of Computer Science and Engineering. Computer Science. CIS4500 Database and Information Systems. The emphasis will be on robotics anatomy and configurations, robotocs kinematics, end effectors, use of sensors in robotics, robotics programming, design of robot workcell, robotics applications to production problems, cost justifications and robotics safety, rather than on the extensive theory of robotics. This is often shown as text on the user's screen and is known as output. It is also suitable for Penn undergraduates in CIS or CE as an upper-level elective. But in reality, people are quickly solving these problems on a huge scale with clever systems and heuristics! Prerequisite: Students should have a good knowledge of object-oriented programming (C++) and basic familiarity with linear algebra and physics. This course investigates how to design efficient algorithms. Students are expected to have a basic understanding of computer architecture and graphics, and should be proficient in OpenGL and C/C++. The goal of this course is to develop a deeper understanding of techniques and concepts used in Computational Biology. Applications to relational databases, modeling reactive systems and program verification are also discussed. The topics include finite automata and regular languages, context-free grammars and pushdown automata, Turing machines and undecidability, tractability and NP-completeness. Covered topics include: practical computer security principles; firewalls, malware, and intrusion detection; cryptography basics and its applications; mobile devices and related security issues; network technologies and their vulnerabilities. MCIS-CS. Topics covered include linear and logistic regression, SVMs, PCA and dimensionality reduction, EM and HMMs, and deep learning. Those who work in computer and information sciences may have an associate degree, a bachelor's degree, or a graduate degree (either a master's degree or a doctorate). CIS5150 Fundamentals of Linear Algebra and Optimization. What useful tools can machine learning develop from databases of art historical images or other datasets of visual culture? This course presents techniques for the design, writing, testing, and debugging of medium-sized programs, and an introduction to data structures (stacks, queues, linked lists) using an object-orientated programming language. The Master of Science (MS) in Computer Information Systems program is designed for students who wish to combine technical competence in information systems with knowledge of managerial and organizational issues. This course investigates algorithms to implement resource-limited knowledge-based agents which sense and act in the world. We will also examine ideas that have been proposed for tomorrow's Web, and we will see some of the challenges, research directions, and potential pitfalls. This course provides an introduction to the broad field of database and information systems, covering a variety of topics relating to structured data, ranging from data modeling to logical foundations and popular languages, to system implementations. One significant programming language is covered in depth. Trost focused his coursework around intrusion detection and protecting computer networks. 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. Our graduates will be qualified to lead and participate in culturally diverse and inclusive teams, becoming global and ethical collaborators. Developing tools for approaching design, analysis, and implementation of embedded systems in a principled manner is an active research area. But how do you create a software "product" as part of a team, with customers that have expectations of functionality and quality? 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. Advanced topics in databases: distributed databases, integrity constraints, failure, concurrency control, relevant relational theory, semantics of data models, the interface between programming of languages and databases. No prior knowledge of quantum mechanics (QM) is assumed. Additional background in statistics, data analysis (e.g., in Matlab or R), and machine learning is helpful (example : ESE5420). (W), Restriction(s): Can enroll if Level is Undergraduate. In this course we will critically examine these assumptions and their consequences for scientific progress. Sample specific topics include: passwords and offline attacks, DES, RSA, DSA, SHA, SSL, CBC, IPSec, SET, DDoS attacks, biometric authentication, PKI, smart cards, S/MIME, privacy on the Web, viruses, security models, wireless security, and sandboxing. This course introduces students to common physically based simulation techniques for animation of fluids and gases, rigid and deformable solids, cloth, explosions, fire, smoke, virtual characters, and other systems. Can you verify that a program has correctly computed a function without ever computing the function? The CIS curricula prepare students to begin careers as computing professionals or to pursue graduate study in the field. 19 General Education courses. Writing a "program" is easy. CIS0099 Undergraduate Research/Independent Study. The Department of Computer and Information Science (CIS) at Penn Engineering is uniquely positioned to propel future intellectual leaders, entrepreneurs, thinkers and innovators to success. The BS in Computer and Information Science program is accredited by the Computing Accreditation Commission of ABET, https://www.abet.org. In Information Science and Technology, the Bachelor of Science degree consists of 120 credit hours. The main focus is on computer science (e.g., basic runtime, space and complexity analysis, programming, and empirical evaluations?. Computer and Information Science PhD Curriculum Program Requirements General Program Requirements: Number of Credits Required Beyond the Baccalaureate: 36 Required Courses: Artificial Intelligence and Applications Track Computer and Network Systems Track Information Systems Track Software Systems Track 1 No permission from the instructor is needed. CIS306 Discrete Structures II 4 Credit Hours. Restriction(s): Can enroll if Class is Junior or SeniorCan enroll if Level is UndergraduateCannot enroll if Major is, CIS436 Mobile App Des & Impl 3 Credit Hours. Variety of students from different majors and schools to bring their diverse skill sets to the programs discipline with sponsor. Algorithms to implement resource-limited knowledge-based agents which sense and act in the preparation of the largestand most new... For building computer systems research area majors and schools to bring their diverse sets. The BA digital library grammars and pushdown automata, Turing machines and undecidability, tractability and...., distributed computing and Information science program is accredited by the computing Commission... This course investigates algorithms to implement resource-limited knowledge-based agents which sense and act in preparation! Is assumed Topic: deep learning EM and HMMs, and digital library s screen and is known as.... 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