Fall 2024 Courses

CSE Fall 2024 Courses

NOTE: This listing represents our current plan for the semester in question. Course offerings and class times are occasionally subject to change for reasons beyond our control.

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COMPUTER SCIENCE COURSE ENROLLMENT INFO FOR NON-MAJORS

Space is extremely limited in our computer science classes and we don’t often have space for students outside the program. Highly qualified non-majors can request space in these classes by contacting our Associate Chair, Prof. Mark Erle.  Please know not all requests can be accommodated due to capacity constraints.

CSE 003 INTRODUCTION TO PROGRAMMING, PART A TR 9:20-10:35, Professor Elroy Sturdivant

Covers the same material as the first half of CSE 007. No prior programming experience needed. Cannot be taken by students who have completed CSE 007.

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CSE 007 INTRODUCTION TO PROGRAMMING, Professor Brian Chen

Problem-solving using the Java programming language. Data types, control flow, methods, arrays, objects, inheritance, breadth of computing. Includes laboratory. If credit is given for   CSE 007 then no credit will be given for CSE 003 nor CSE 004.  

CSE 007-110 (Lecture), MW 12:10-1:25, and one of the following labs:

CSE 007-112, R 1:35-2:50

CSE 007-113, R 3:00-4:15

CSE 007-114, F 12:10-1:25

CSE 007-115, R 9:20-10:45

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CSE 012-010/398-035 INTRO TO PROGRAMMING WITH PYTHON TR 3:00-4:15, Professor Masoud Yari

This course provides a project-based exploration of fundamental concepts in computing and "computational thinking." Topics include but are not limited to networks, data visualization, information storage and retrieval, and the popular Python programming language. Each project presents applications of computing in solving real life problems. In this course you will learn to write Python code to visualize data from different sources. You will learn how information is transferred across networks and how to store and retrieve data from relational database management systems. Optional Structured Study Groups will be provided for students who express interest.

CSE 017 PROGRAMMING AND DATA STRUCTURES, Professor Kallie Ziltz

This course is a programming-intensive exploration of software design concepts and implementation techniques. It builds on the student's existing knowledge of fundamental programming. Topics include object-oriented software design, problem-solving strategies, algorithm development, and classic data structures. Prerequisites: CSE 004 or CSE 007 or (CSE 002 and (CSE 001 or CSE 012 or ENGR 010)).

CSE 017-110 (Lecture), T 9:20-10:35, and one of the following recitations:

CSE 017-112, W (Lab) 1:35-2:50

CSE 017-113, W (Lab) 3:00-4:15

CSE 017-114, R (Lab) 9:20-10:35

CSE 017-115, R (Lab) 10:45-12:00

CSE 017-116, R (Lab) 1:35-2:50

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CSE 109 SYSTEMS SOFTWARE, Professor Mark Erle

Advanced programming and data structures, including dynamic structures, memory allocation, data organization, symbol tables, hash tables, B-trees, data files. Object-oriented design and implementation of simple assemblers, loaders, interpreters, compilers and translators. Practical methods for implementing medium-scale programs. Prerequisites: CSE 017

CSE 109-110, (Lecture), MW 1:35-2:50, and one of the following recitations:

CSE 109-113, W (Lab) 7:15-8:30pm

CSE 109-114, R (Lab) 7:15-8:30pm

CSE 140 FOUNDATIONS OF DISCRETE STRUCTURES ALGORITHMS, Professor Arielle Carr

Basic representations used in algorithms: propositional and predicate logic, set operations and functions, relations and their representations, matrices and their representations, graphs and their representations, trees and their representations. Basic formalizations for proving algorithm correctness: logical consequences, induction, structural induction. Basic formalizations for algorithm analysis: counting, pigeonhole principle, permutations. Prerequisites: (MATH 021 or MATH 031 or MATH 051 or MATH 076) and CSE 017. CSE 017 can be taken concurrently.

CSE 140-110, (Lecture) MW 9:20-10:35 

CSE 140-115, (Lecture) MW 10:45-12:00

CSE 160-010 INTRO TO DATA SCIENCE, Professor Aparna Bharati

Interested in understanding the hype about data science, big data, or data analytics? This course introduces you to data science, a fast-growing and interdisciplinary field, focusing on the computational analysis of data to extract knowledge and insight. You will be introduced to the collection, preparation, analysis, modeling, and visualization of data, covering both conceptual and practical issues. Applications of data science across multiple fields are presented, and hands-on use of statistical and data manipulation software is included. The course is open to students from all areas of study; the only prerequisite is some programming experience (automatic if you've taken CSE 004, 007, 012 or BIS 335, or permission of the instructor is available if you can show that you've successfully completed a programming course online, in high school, or elsewhere). Prerequisites: CSE 004 or CSE 007 or CSE 012 or BIS 335

CSE 160-010, (Lecture) MW 10:45-12:00 and one of the following recitations:

CSE 160-060, F (Lab) 9:50-11:05

CSE 160-061, F (Lab) 12:40-1:55

CSE 202 COMPUTER ORGANIZATION AND ARCHITECTURE, Professor Jialiang Tan

Interaction between low-level computer architectural properties and high-level program behaviors: instruction set design; digital logics and assembly language; processor organization; the memory hierarchy; multicore and GPU architectures; and processor interrupt/exception models. Prerequisites: CSE 017

CSE 202-011, TR 10:45-12:00

CSE 216-110 SOFTWARE ENGINEERING, Professor Stephen Urban

The software life-cycle; life-cycle models; software planning; testing; specification methods; maintenance. Emphasis on team work and large-scale software systems, including oral presentations and written reports. Prerequisites: CSE 017

CSE 216-110, (Lecture) MW 3:00-3:50 and one of the following recitations:

CSE 216-112, M 7:15-9:55pm

CSE 216-113, T 7:15-9:55pm

CSE 252-010 COMPUTERS, INTERNET AND SOCIETY

An interactive exploration of the current and future role of computers, the Internet, and related technologies in changing the standard of living, work environments, society and its ethical values. Privacy, security, depersonalization, responsibility, and professional ethics; the role of computer and Internet technologies in changing education, business modalities, collaboration mechanisms, and everyday life. (SS).

CSE 252-010, MW 12:10-1:25, Professor Dominic DiFranzo

CSE 252-011, TR 1:35-2:50, Professor Elroy Sturdivant

CSE 252-012, MW 10:45-12:00, Professor Kallie Ziltz

CSE 262-110 PROGRAMMING LANGUAGES, Professor Corey Montella

Use, structure and implementation of several programming languages. Prerequisites: CSE 017

CSE 262-110 (Lecture) MW 10:45-12:00 and one of the following recitations:

CSE 262-111, M 3:00-4:15

CSE 262-112, W 1:35-2:50

CSE 264 WEB SYSTEMS PROGRAMMING, MW 3:00-4:15, Professor Dominic DiFranzo

Practical experience in designing and implementing modern Web applications. Concepts, tools, and techniques, including: HTTP, HTML, CSS, DOM, JavaScript, Ajax, PHP, graphic design principles, mobile web development. Not available to students who have credit for ISE 275. Prerequisites: CSE 017

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CSE 265-010 SYSTEM AND NETWORK ADMINISTRATION 

Overview of systems and network administration in a networked UNIX-like environment. System installation, configuration, administration, and maintenance; security principles; ethics; network, host, and user management; standard services such as electronic mail, DNS, and WWW; file systems; backups and disaster recovery planning; troubleshooting and support services; automation, scripting; infrastructure planning. Prerequisites: CSE 017

CSE 265-010, (Lecture) TR 12:10-1:35 and the following recitation:

CSE 265-060, F 12:10-1:25

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CSE 281 CAPSTONE PROJECT II, TR 3:00-4:15, Professor George Witmer

Second of a two semester capstone course sequence that involves the design, implementation, and evaluation of a computer science software project; conducted by small student teams working from project definition to final documentation; each student team has a CSE faculty member serving as its advisor; The second semester emphasis is on project implementation, verification & validation, and documentation requirements. It culminates in a public presentation and live demonstration to external judges as well as CSE faculty and students. Prerequisites: CSE 280

CSE 303-010 OPERATING SYSTEM DESIGN, MW 1:35-2:50, Professor Houria Oudghiri

Process and thread programming models, management, and scheduling. Resource sharing and deadlocks. Memory management, including virtual memory and page replacement strategies. I/O issues in the operating system. File system implementation. Multiprocessing. Computer security as it impacts the operating system.  Prerequisites: ECE 201 or (CSE 201 or CSE 202) and CSE 109.

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CSE 318/418 INTRODUCTION TO THEORY OF COMPUTATION, TR 12:10-1:25, Professor James Femister

Provides a deep understanding of computation, its capabilities and its limitations. The course uses discrete formal methods to (1) formulate precise definitions of three kinds of finite-state machines (finite automata, pushdown automata, and Turing machines); (2) prove properties of these machines by studying their expressiveness (i.e., the kinds of problems that can be solved with these machines), and (3) study computational problems that cannot be solved with algorithms. Prerequisites: CSE 140

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CSE 320/420 BIOMEDICAL IMAGE COMPUTING AND MODELING, TR 9:50-11:05, Professor Lifang He

Biomedical image modalities, image computing techniques, and imaging informatics systems. Understanding, using, and developing algorithms and software to analyze biomedical image data and extract useful quantitative information: Biomedical image modalities and formats; image processing and analysis; geometric and statistical modeling; image informatics systems in biomedicine. Credit will not be given for both CSE 320 and CSE 420. Prerequisites: (MATH 205 or MATH 043) and CSE 017

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CSE 326/426 FUNDAMENTALS OF MACHINE LEARNING, TR 10:45-12:00, Professor Lichao Sun

Bayesian decision theory and the design of parametric and nonparametric classification and regression: linear, quadratic, nearest-neighbors, neural nets. Boosting, bagging. Credit will not be given for both CSE 326 and CSE 426. Prerequisites:  CSE 017 and (MATH 205 or MATH 043) and (MATH 231 or ISE 121 or ECO 045)

CSE 327-010 ARTIFICIAL INTELLIGENCE THEORY AND PRACTICE, MW 11:15-12:30, Professor Jeff Heflin

Introduction to the field of artificial intelligence: Problem solving, knowledge representation, reasoning, planning and machine learning. Use of AI systems or languages. Advanced topics such as natural language processing, vision, robotics, and uncertainty. Credit will not be given for both CSE/COGS 127 and CSE/COGS 327. Prerequisites: CSE 017 and CSE 140

CSE 340 DESIGN AND ANALYSIS OF ALGORITHMS, Professor Ahmed Hassan

Algorithms for searching, sorting, manipulating graphs and trees, finding shortest paths and minimum spanning trees, scheduling tasks, etc.: proofs of their correctness and analysis of their asymptotic runtime and memory demands. Designing algorithms: recursion, divide-and-conquer, greediness, dynamic programming. Limits on algorithm efficiency using elementary NP-completeness theory. Prerequisites:(MATH 021 or MATH 031 or MATH 076) and CSE 140 and CSE 017

CSE 340-110 (Lecture) MW 9:20-10:35 and one of the following recitations:

CSE 340-112, F 9:20-10:35

CSE 340-113, F 10:45-12:00

CSE 340-114, F 12:10-1:25

CSE 342-010 FUNDAMENTALS OF INTERNETWORKING, MW 12:10-1:25

Architecture and protocols of computer networks. Protocol layers; network topology; data-communication principles, including circuit switching, packet switching and error control techniques; sliding window protocols, protocol analysis and verification; routing and flow control; local and wide area networks; network interconnection; client-server interaction; emerging networking trends and technologies; topics in security and privacy. Prerequisites: CSE 109

CSE 348-010 AI GAME PROGRAMMING, MW 1:35-2:50, Professor Stephen Lee-Urban

Contemporary computer games: techniques for implementing the program controlling the computer component; using Artificial Intelligence in contemporary computer games to enhance the gaming experience: pathfinding and navigation systems; group movement and tactics; adaptive games, game genres, machine scripting language for game designers, and player modeling. Credit will not be given for both CSE 348 and CSE 448. Prerequisites: CSE 327 or CSE 109

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CSE 349/449 BIG DATA ANALYTICS, MW 2:05-3:20, Professor Daniel Lopresti

Provides working knowledge of large-scale data analysis using open source frameworks such as Apache Spark and Waikato Environment for Knowledge Analysis (Weka). Includes patterns employed in big data analytics, including classification, collaborative filtering, recommender systems, natural language processing, simulation, deep learning, and anomaly detection. Project-oriented software course; students should have substantial programming experience in one or more high-level languages. Past experience in data mining and/or machine learning expected. Credit will not be given for both 349 and 449. Prerequisites: CSE 109 and (CSE 326 or CSE 327)

CSE 367/467 BLOCKCHAIN PROJECTS, F 10:45-12:00, Professor Hank Korth

Independent or small-group unique projects related to blockchain systems and/or applications. While pursuing their own project, students serve as consultants to the other teams via a once-weekly class meeting in which each team presents updates on status, progress, and open problems, and one student gives a longer prepared presentation on current research or development results in the blockchain field. Each project team has its own separate second weekly meeting with the instructor for a more in-depth project review and discussion. Prerequisites: CSE 242 and Department permission (to be granted only after the student has agreed with the instructor on a specific project team and agenda).

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CSE 371/471 PRINCIPLES OF MOBILE COMPUTING, MW 9:20-10:35, Professor Mooi Choo Chuah

Fundamental concepts and technology underlying mobile computing. Current research in these areas. Examples drawn from a variety of application domains such as health monitoring, energy management, commerce, and travel. Issues of system efficiency will be studied, including efficient handling of large data such as images and effective use of cloud storage. Recent research papers will be discussed. Credit will not be given for both CSE371 and CSE471. Prerequisites: CSE 109 and (CSE 202 or CSE 201) 

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CSE 406-010 RESEARCH METHODS, MW 3:30-4:45, Professor Daniel Lopresti

Technical writing, reading the literature critically, analyzing and presenting data, conducting research, making effective presentations, and understanding social and ethical responsibilities. Topics drawn from probability and statistics, use of scripting languages, and conducting large-scale experiments. Must have first-year status in either the CS or CompE Ph.D program.

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CSE 411-010 ADVANCED PROGRAMMING TECHNIQUES, TR 9:50-11:05, Professor Corey Montella

Deeper study of programming and software engineering techniques. The majority of assignments involve programming in contemporary programming languages. Topics include memory management, GUI design, testing, refactoring, and writing secure code.

 

 

CSB COURSES – Fall 2024

CSB 304 TECHNOLOGY AND SOFTWARE VENTURES, TR 10:45-12:00, Professor Joshua Ehrig

Designed from the perspective of functional leaders, course provides a holistic perspective of developing successful software ventures across various industries in an interdisciplinary and experiential environment. Students develop a software-oriented idea, concurrent with module delivery containing best practices, case studies, and subject-matter experts. Examines business model fundamentals, customer discovery, translating requirements to a minimum viable product, agile development, user acquisition, and traction. ENTP Capstone. Prior programming experience or technical background not required. Open to students in any college and major. Prequisites: ENTP 101 or CSE 002 or BIS 111

CSB 313 DESIGN OF INTEGRATED BUSINESS APPLICATIONS II. TR 3:00-4:15, Professor George Witmer

Integrated Product Development (IPD) Capstone Course II. This course extends the industry-based project initiated in CSB 312 into its implementation phase. Detailed design, in-house system construction and delivery, commercial software options, and systems maintenance and support. The practical component of the course is supplemented by several classroom-based modules dealing with topics that lie at the boundary of computer science and business. Formal, oral, and written presentations to clients. Prerequisites: CSB 312

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