A significant discussion of algorithm complexity theory, including time and space trade-offs and elementary computability theory, is included. In making your plans to enroll at the University of Michigan and to better manage your process, the following estimated costs and fees will help you determine you and your family’s potential financial plans. Using various modern software tools, students will apply various design patterns to real-world software design problems to gain complete practical understanding. At least two weeks prior to registration in the semester when such a course is to be elected, an interested student must submit to the CIS chair and one CIS faculty member a written request for permission to elect a research course on the appropriate form available in the CIS Office. Topics include principles of program design, coding, debugging, testing, and documentation. This is a microcomputer literacy course with primary emphasis on the application tools of the word processor, spreadsheets, and database. Required courses in the Computer and Information Science (CIS) major stress theory and application, as well as the role of other fields such as mathematics, statistics, electrical and computer engineering, business, and software engineering, among others. (F,W), CIS 290     Topic in Programming Languages     2 Credit Hours. Students are introduced to the Unified Modeling Language for requirements analysis using use-cases and activity diagrams, an object-oriented programming language for data science applications, and the fundamentals of computer hardware, system software, and components. Student works with industrial sponsor in the area of CIS. (F,W,S), CIS 200     Computer Science II     4 Credit Hours. For specific topic, consult current semester's Schedule of Classes. 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. CIS 2001 CS II for Data Scientists 4 Credit Hours. (F, W, S), CIS 4981     Design Seminar for CIS-DS I     2 Credit Hours, Full Course Title: Design Seminar for Dual Degree CIS-DS Majors I Seminar topics discussed include: computing ethics and professional practice in software engineering. The course discusses classical relational technologies, and then covers the more current approaches to managing massive amounts of data for analytics purposes. Basic geometrical concepts: graphics output primatives, two-dimensional transformations, windowing and clipping, three-dimensional viewing, visible surface detection methods, and graphical user interfaces. The course will introduce both knowledge-based and statistical approaches to NLP, illustrate the use of NLP techniques and tools in a variety of application areas, and provide insight into many open research problems. (F). The particular language changes from term to term. Data design topics include object-oriented discussions of hashing, advanced tree structures, graphs, and sets. The course will contain an overview of one AI language and some discussion of important applications of artificial intelligence methodology. 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. The principles of UML modeling are continued. Grades will be granted on a Pass/Fail (S/E) basis exclusively. Contact > Intranet > Electrical and Computer Engineering EECS Building 1301 Beal Avenue Topics include an overview of the internet, congestion control, quality of service, internet multicasting, multimedia networking, mobile and wireless networks, vehicular networks, overlay networks, peer-to-peer networks, internet management (SNMP), and internet applications (web-HTTP and email-SMTP). Prerequisite(s): (CIS 200 or ECE 270) and (CIS 310* or ECE 370* or ECE 372*), Restriction(s): Cannot enroll if Class is FreshmanCan enroll if Level is Undergraduate, CIS 390     Topics in Computer Science     1 to 3 Credit Hours. This course is a second registration for a research project in CIS. CIS students must choose a concentration in Computer Science, Information Systems or Game Design. (F,W,S). See a feed of new offerings from EECS faculty, including the upcoming term. These courses are usually outside the traditional engineering, math, and science courses. A search tool that provides information on LSA courses. Seminar topics discussed include: computing ethics and professional practice in software engineering. Students will examine in-depth concepts in Internet evidence collection and preservation, as well as applications of contemporary commercial forensic investigative software. CIS 310     Computer Org and Assembly Lang     4 Credit Hours. Below are descriptions of selected courses offered by the EECS department. This is a 1-credt hour seminar designed to teach students the essentials of using a computer effectively for EECS students. Course Name sort desc Number Term Credit Hrs; Applied Microeconomics: BE 501 : Summer 19 +1: 3 hours : Applied Microeconomics --- This course provides … EECS course descriptions in the bulletin >. An introduction to calculus (MATH 115) is required and does not count toward the 24 hours. Topics include principles of program design, coding, debugging, testing, and documentation. A course designed to offer selected topics in an area of computer science. Lexical analysis, top-down and bottom-up parsing, code generation and optimization. Introduction to compiler-writing tools such as LEX and YACC. Prerequisite(s): CIS 375 and (CIS 421* or CIS 422*), Restriction(s): Cannot enroll if Class is Freshman or Sophomore, CIS 427     Comp Networks and Dis Process     4 Credit Hours. (YR). Various forms of software will be considered in this class including high level applications and system software. The course includes numerous seminars by notable practitioners. Overview of digital computer hardware and system software components: machine architecture, operating systems, computer networks, data security, and performance evaluation. Applications to relational databases, modeling reactive systems and program verification are also discussed. Students will participate in a final project. While the target audience is EE/CE/CS/DS students, any student wishing to learn how to use their computer more effectively is encouraged to join. Permission of instructor required. Please contact us at is-michigan@umich.edu during this time and reach out to is-advising@umich.edu with any questions for the International Studies advisors. THis course provides a practical introduction to a broad range of security topics including legal, ethical and professional issues in information security. The program encourages innovation on the part of students, prepares students for graduate education, trains students to communicate effectively, and provides students with the tools needed to become leaders in their profession. PICS Funding PICS helps fund its students to study, research, and intern abroad. This course is a continuation of Digital Forensics I and will focus on Internet Forensics. Grad Course List. Prerequisite(s): CIS 350 or CIS 3501 or IMSE 350 or (ECE 270 and ECE 276) or (ECE 370 and MATH 276), CIS 491     Research Project I     1 to 4 Credit Hours. (F,W,S), CIS 3501     Data Struc & Alg Anlys for SE     4 Credit Hours, This course focuses on data design and algorithm design for software engineers. (F,W,S). (F,W,S), Prerequisite(s): CIS 375 and CIS 3200 and (STAT 325 or IMSE 317) and CIS 310 and (CIS 427 or CIS 450), CIS 4982     Design Seminar for CIS-DS II     2 Credit Hours, Dual Degree CIS and Data Science students participate in the design and implementation of a major software project involving data science. The computer science (CS) program at the University of Michigan is available to students in both the Colleges of Engineering and of Literature, Science, and the Arts. Students must elect different topics to take both CIS 390 and CIS 391. Three-hour lecture and three-hour laboratory per week. The CIS curricula prepare students to begin careers as computing professionals or to pursue graduate study in the field. Prerequisite(s): (MATH 217 or MATH 227 or MATH 228) and (CIS 350 or CIS 3501 or IMSE 350) or (ECE 370 and MATH 276) or (ECE 370 and ECE 276), CIS 452     Inf Vis & Multimedia Gaming     3 Credit Hours. The courses are divided into the 12 research areas a graduate student can major in. 3 Credit Hours, Full Title: Practical Aspects of Computer Security Concentration requirements are listed below. This course will consist of three lecture hours and one two-hour laboratory. No credit for CIS majors. Computing professionals offer expertise in the effective and efficient use of computers for solving human problems, whether that be as a member of a project development team, as a builder of powerful and easy-to-use tools, as an individual researcher, or as an educator. The focus of the course will be hands-on development of computer games. This course will consist of three lecture hours and one two-hour laboratory. For questions regarding course work completed during the COVID-19 crisis, please visit this page. The course will consist of three lecture hours and one two-hour laboratory. (F,W,S). From mobile apps to bitmaps, this course explores computational technologies and how they impact society and our everyday lives. Programming language design. Topics include database environments, database design, the relational data model, normalization, SQL, query processing, parallel databases and query processing, in-database analytics, data warehousing, key-value and column stores, NoSQL and NewSQL approaches for managing massive data. The specific topics will be announced (together with special prerequisites) each time offered. Prerequisite(s): MATH 115* or MATH 113* or Mathematics Placement with a score of 116, CIS 1501     CS I for Data Scientists     4 Credit Hours, This course provides a foundation for further studies in computer and information science and emphasizes a structured approach to problem solving and algorithm development using a high-level language more suited to data science applications. Prerequisite(s): (CIS 350 or IMSE 350 or CIS 3501) or (ECE 370 and MATH 276) or (ECE 370 and ECE 276), CIS 405     Algorithm Analysis & Design     3 Credit Hours. Communicate effectively in a variety of professional contexts. Prerequisite(s): (CIS 350 or CIS 3501 or IMSE 351) or (ECE 370 and MATH 276) or (ECE 370 and ECE 276) and IMSE 317, CIS 435     Web Technology     3 Credit Hours. Success in this course requires a mature understanding of software systems. 303 E. Kearsley Street Flint, MI 48502-1950. This course provides a foundation for further studies in computer and information science and emphasizes a structured approach to problem solving and algorithm development. Topics covered include: database environments, ER modeling, relational data model, object-oriented databases, database design theory and methodology, database languages, query processing and optimization, concurrency control, database recovery, and database security. The LSA Course Guide will help you find available classes searchable by subject, instructor, keyword, and more. The main focus is on computer science (e.g., basic runtime, space and complexity analysis, programming, and empirical evaluations?. An introduction to the Python programming language and its various libraries, packages, and tookits. Seminar topics discussed include: computing ethics and professional practice. (F). This page provides a list of graduate-level ECE courses. This course introduces basic techniques for digital animation, computer and video games, and web multimedia. General Education Program: The Dearborn Discovery Core, College of Education, Health, and Human Services, College of Engineering and Computer Science, Capsule History of the University of Michigan-​Dearborn, College of Engineering and Computer Science, Dearborn Discovery Core (General Education), The Regents of the University of Michigan, Information Visualization and Virtualization. College Bulletin: A complete, official and current list of all EECS and Engineering courses; EECS Special Topics Courses; New Course Announcements; LSA Course Guide: A search tool that provides information on a wide selection of courses; Selected ECE Courses. CONTACT US. Prerequisite(s): CIS 310 and (CIS 350 or CIS 3501 or IMSE 350) or (ECE 370 and MATH 276) or (ECE 370 and ECE 276) and IMSE 317*, CIS 451     Computer Graphics     3 Credit Hours. Restriction(s): Cannot enroll if College is Business, CIS 446     Wireless & Mobi Comp Security     3 Credit Hours, Full course title: Wireless and Mobile Computing Security. Performance in these classes is indicative of student aptitude for the Computer Science program, and students who do not perform well are encouraged to meet with a CS-LSA advisor. 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. (F,W). The focus of this course will be on the development of analytics/data science applications. These are: EECS 203, EECS 280, MATH 115, MATH 116. Apply computer science theory and software development fundamentals to produce computing-based solutions. The following abbreviations are used to denote the frequency of offering: (F) fall term; (W) winter term; (S) summer term; (F, W) fall and winter terms; (YR) once a year; (AY) alternating years; (OC) offered occasionally. Students are provided with support and encouragement in exploring their options and learning to make informed decisions. Computer Science and Engineering Bob and Betty Beyster Building 2260 Hayward Street Ann Arbor, MI 48109-2121 The course will cover three major areas: software attacks and defenses, program analysis, and software verification. NOTE: how courses will be delivered is subject to change pending potential updates to University policy in the near future. (W), Restriction(s): Can enroll if Class is Junior or SeniorCan enroll if College is Engineering and Computer ScienceCannot enroll if Major is, CIS 490     Advanced Topics     1 to 3 Credit Hours. Prerequisite(s): CIS 350 or CIS 3501 or IMSE 350 or (ECE 370 and MATH 276) or (ECE 370 and ECE 276), CIS 481     Computational Learning     3 Credit Hours, This course covers basic computational aspects of learning to perform a task and improve with experience. The course will consist of three lecture hours and one two-hour laboratory. Analysis of case studies will also be discussed. Topics include fundamentals of artificial intelligence, knowledge representation and knowledge processing, tools for building expert systems (logic programming, expert shells), decision support system design (modeling and simulation), expert system design (knowledge engineering, learning). The principles of UML modeling are continued. CIS 425     Information Systems     4 Credit Hours. Four additional science credits; must be a different subject than the two course sequence prerequisite: Any 100 to 400 level course with no more than 6 credits, as needed to get a minimum of 120 credits for graduation. Seminar topics discussed include: computing ethics and professional practice in data science. (OC). CIS 112     Computer Literacy/Info Mgmt     3 Credit Hours. Topics covered include pointers, templates, and inheritance. The CIS chair will review the proposal with faculty members to ascertain availability of relevant faculty supervision and to establish appropriate credit. M = Counts as a Major Area course automatically E = Counts as a Major Area course after approval by an advisor. The curriculum is modeled on the recommendations of the two main professional computing societies, the Association of Computing Machinery (ACM) and the Institute for Electrical and Electronic Engineering (IEEE). (YR), Restriction(s): Can enroll if College is Engineering and Computer Science, CIS 3200     Data Science II     4 Credit Hours, This course provides an overview of what Big Data is and explores its characteristics. 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