It is also suitable for Penn undergraduates in CIS or CE as an upper-level elective. The focus is on topics in machine learning theory for researchers and students in artificial intelligence, neural networks, theoretical computer science, and statistics. Python is an elegant, concise, and powerful language that is useful for tasks large and small. Along the way, we study objects and inheritance, first-class functions (closures), data representation and runtime-support issues such as garbage collection. CS 101 | Intro to Computers & Information Technology 5 Credits. The RTL (register transfer level) approach. This course is appropriate as an upper-level undergraduate CIS elective. Extensive hands-on work with SQL databases. The Independent Study should not be used for ongoing research towards a thesis, for which the CIS 999 designation should be used. In the second half of the course, students work in teams to conceptualize and develop a significant mobile application. The minor may be combined with any major or minor except information technology. 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. How do you find shortest paths in a map? We introduce the basic concepts about complexity of an algorithm and methods on how to compute the running time of algorithms. In addition to exploring general concepts of archaeology and the media, students will work in teams to produce an interactive, digital media exhibit using the latest modeling visualization programs for presenting the sacred landscape of the Inca capitalof Cuzco, Peru. Theory of computable functions and effectively enumerable sets. This course develops students problem solving skills using techniques that they have learned during their CS training. authoritative source of information about course offerings, option requirements, graduation requirements, program is appropriate for students desiring a strong concentration in the core areas of computer science—algorithms, programming languages, and systems—with more courses in computer science, computer engineering, and computational media; this program also allows for a few electives outside of science and engineering. The second half will focus on Rails. Tutorials of software and hardware tools employed in the course. TECM 1700 - Introduction to Professional, Science, and Technical Writing The course assumes mathematical and programming experience equivalent to CIS160 and CIS121. A self-paced lab that provides students with extra practice and supervision in transferring their programming skills to a particular programming language. This course covers the basics of computer programming and provides a foundation for further learning in this area. This course can (with approval) be used to satisfy the project requirement for the CS major. The primary goal of this course is to introduce computational methods of interacting with data. The course will focus on basic foundational concepts underpinning and motivating modern machine learning and data mining approaches. Both theoretical and algorithmic aspects will be discussed. All ar welcome, including those with no programming experience. Along the way, students will also pick up essential skills such as git, bash, HTML and CSS. Topics include algebraic block codes, e.g., Hamming, BCH, Reed-Solomon (including a self-contained introduction to the theory of finite fields); and the modern theory of sparse graph codes with iterative decoding, e.g. This course is intended to give the student a basic understanding of the major hardware and software principles involved in the specification and design of embedded systems. During the later semesters, students take elective computer science courses … It's interactive, fun, and you can do it with your friends. Freshmen standing. Introduction to the central ideas, practices, and impact of computer science and computational thinking. This is a paper reading course, and students are expected to understand material directly from research articles. Senior standing or permission of instructor. Knowledge of computer organization and basic programming skills. Prerequisite: Previous exposure to major concepts inn linear algebra (i.e. Potential class projectinclude fly-throughs of architectural and landscape renderings, simulations of astronomy and cosmology, modeling of human behavior within architectural and landscape settings, and study artifacts in the Penn Museum. Overview of classical complexity theory, quantum complexity, efficient quantum algorithms, fault-tolerant quantum computation, physical implementations of quantum computation. Sometimes, deep learning is a product; sometimes, deep learning optimizes a pipeline; sometimes, deep learning provides critical insights; sometimes, deep learning sheds light on neuroscience or vice versa. 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. To enroll in CIS 410, students must develop an abstract of the proposed work, and a member of the CIS graduate group must certify that the work is suitable and agree to supervise the project; a second member must agree to serve as a reader. 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. Mathematics with Computer Science (Course 18- C) Physics (Course 8) Interdisciplinary Programs; Chemistry and Biology (Course 5- 7) Computation and Cognition (Course 6- 9) Computer Science and Molecular Biology (Course 6- 7) Computer Science, Economics, and Data Science (Course 6- 14) Students will be expected to display knowledge of both theory and practice through written examinations and programming assignments. Methods for identifying intractability (via NP-completeness) will be discussed. Computer vision technology has led to latest innovations in areas such as Hollywood movie production, medical diagnosis, biometrics, and digital library. CIS 261 Discrete Probability, Stochastic Processes, and Statistical Inference. The course expects students to be comfortable with graph theory, probability, and basic programming. Assignments will include problems drawn from fields such as graphics, numerics, networking, and games. Bachelor of Science in Computer Science with Threads. Basic programming experience. Overview of classical information theory, compression of quantum information, transmission of quantum information through noisy channels, quantum error-correcting codes, quantum cryptography and teleportation. This course is appropriate as an upper-level undergraduate CIS elective. CIS 549 Wireless Communications for Mobile Networks and Internet of Things. CIS 398 Quantum Computer and Information Science. Prerequisites: for Ma/CS 6 c, Ma/CS 6 a or Ma 5 a or instructor's permission. This course is an introduction to quantum cryptography: how to use quantum effects, such as quantum entanglement and uncertainty, to implement cryptographic tasks with levels of security that are impossible to achieve classically. The lectures will cover relevant background material at an advanced level and present results from selected recent papers within that year's chosen theme. Side information in source coding and communications. This course is a broad introduction to all aspects of computer systems architecture and serves as the foundation for subsequent computer systems courses, such as Digital Systems Organization and Design (CIS 371), Computer Operating Systems (CIS 380), and Compilers and Interpreters (CIS 341). Students are expected to have a basic understanding of computer architecture and graphics, and should be proficient in OpenGL and C/C++. After a brief introduction to the language, programming assignments wil l be in Python. Basic material includes mathematical techniques for analyzing performance in terms of resources, such as time, space, and randomness. Throughout the term students will work within an interdisciplinary team of their peers to conceive an innovative digital product concept and produce a business plan and a working prototype. This course could be taken immediately following CIS 160. One time course offerings of special interest. The course builds upon existing implementations of basic data structures in JAVA and extends them for the structures like trees, studying the performance of operations on such structures, and theiefficiency when used in real-world applications. Advanced digital design as it applies to the design of systems using PLDs and ASICs (in particular, gate arrays and standard cells). CIS 515 Fundamentals of Linear Algebra and Optimization. It is aimed at second-year undergraduates. Prerequisites: Ma 5 or equivalent, or instructor's permission. 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. See also: UW Course Catalog. Approval of student's research adviser and option adviser must be obtained before registering. 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. Computation and Programming will play an essential role in this course. This course will explore three topics: 1) image morphing, 2) image matching and stitching, and 3) image recognition. (3) How to characterize the equilibrium points of the model? Prerequisites: Ma 2, Ma 3 or instructor's permission. The course has a strong hands-on component, in the form of homework assignments and a final project. The course will cover fundamentals of algorithms, statistics, and mathematics as applied to biological problems. Catalog; Courses; Computer Science; Computer Science Courses View/Print PDF. Enrollment for students participating in Teaching Practicum. The course includes weekly written and programming assignments covering the lecture material. 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. CIS 610 Advanced Geometric Methods in Computer Science. Topics from coding and cryptography, including Hamming codes and RSA. This course introduces the theory and practice of formal methods for the design and analysis of concurrent and embedded systems. It presents selected topics from these domains, focusing on their integration into a full sense-think-act robot. At the end of the course, students will be ready to learn other programming languages in courses such as CS 11, and will also be ready to take more in-depth courses such as CS 2 and CS 4. More advanced students may propose their own programming project as the target demonstration of their new language skills. We will introduce the security definition for quantum key distribution and see protocols and proofs of security for this task. CS 179 E-Z Project in Computer Science (4 units maximum) *Technical Electives not in the Catalog for 2020-2021 Intermed. This course provides firm foundations in linear algebra and basic optimization techniques. Graded pass/fail. This course investigates computation by molecular systems, emphasizing models of computation based on the underlying physics, chemistry, and organization of biological cells. The course covers four major areas: fundamentals of cryptography, security for communication protocols, security for operating systems and mobile programs, and security for electronic commerce. proof-of-time, proof-of-space, proof-of-stake) will be explored and analyzed. Grades are based on technical writing skills (as per submitted report), oral presentation skills (as per class presentation) and progress on the project. This course is appropriate as an upper-level undergraduate CIS elective. In the systems part, the students will build a software simulator of Internet routing and congestion control algorithms. or B.S.E. 6 units (2-2-2): second, third terms. These are evaluated by the Project Adviser and the Course Instructor. The students will be expected to use the Maple programming environment in homework exercises which will include: numerical and symbolic computations, simulations, and graphical displays. 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. Deviation bounds, k-wise independence, graph problems, identity testing, derandomization and parallelization, metric space embeddings, local lemma. The second part will focus on Rails, the web framework and will include all topics required to develop and deploy production-ready modern web applications with Rails. Each student will be responsible for presenting one primer and at least two SIGGRAPH papers to the class. This course is an introduction to the theory of Machine Learning, a field which attempts to provide algorithmic, complexity-theoretic and statistical foundations to modern machine learning. These are evaluated by the Project Adviser and the Course Instructor. Entropy, relative entropy, and mutual information for discrete and continuous random variables. : Introduction to Computational Biology and Bioinformatics. It is being increasingly used in industry by organizations such as Facebook, AT&T, and NASA, along with several financial firms. The course combines an introduction to basic theory with a hands-on emphasis on learning how to use these methods in practice so that students can apply them in their own work. Every year the course and projects focus on a particular emerging technology theme. Through Rails, we'll ex;ore the "culture" of web programming such as agile methodology, testing, key aspects of software engineering, using web services and APIs, and deploying to the cloud. Computational cameras overcome the limitations of traditional cameras, by moving part of the image formation process from hardware to software. Prerequisite: ESE 407 or CIS 505 or 551 or 553, CIS 550 Database and Information Systems, 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. 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. Filters, equalization detailed study of FPGA devices and comparison to ASIC alternatives the past failure. To English ) database schema design and analysis of algorithms it to practic systems programming.... Four ( 4 ) how to program, but do you know how to prove the stability of semester! Topics include finite automata and regular languages, context-free grammars and pushdown automata, Turing machines and RAM,! 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