The Master Program in computer science emphasizes software development, theoretical foundations of computer science and cyber security. It is designed to prepare students for professional positions in industry, government and business, and to provide preparation for graduate work at the doctoral level.
Foundational Knowledge Requirements:
All students admitted into the Davenport University Master of Science in Computer Science are expected to have the necessary undergraduate preparation, as outlined in the Admissions Requirements, prior to entering the 600-level courses. Students without a BS in Computer Science may need to complete the following courses before beginning 600-level courses:
General topics in computer architecture, memory systems design and evaluation, pipeline design techniques, RISC architectures, vector computers, VLSI systems architecture, bootloader, device drivers and I/O. Advanced topics may include: processes and threads, CPU scheduling; process synchronization; deadlock, threads, memory management; cache; main memory; virtual memory; virtual machine; shared-memory and message-passing based parallelism; clusters; database concepts; security and protection; authentication; and cloud computing. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees.
The study of the principles, designs, implementations, performance and security issues and areas of current research in computer networks. This may include various types of computer buses, local area networks, long haul networks and layered network models. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees.
This course covers the theory of computer science emphasizing automata, grammars computation and their applications in the specification of languages and computer systems, models of computation and complexity. Finite-state machines, pushdown automata, Turing machines, regular expressions, decidability, computational complexity, including classes P, NP, NP-complete, NP-hard, and PSPACE will be explored. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees.
This course will study the design and analysis of algorithms, their correctness, their limitations and their relationship to other algorithms. Students will learn how to analyze a problem and determine its reducibility to a common problem with a current solution. Topics covered may also include Computational Geometry, NP-Completeness, Approximation Algorithms, Dynamic Programming, Greedy Algorithms and Reductions. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees.
3
Thesis/Project (More details on the Master Research Thesis or Master Project may be found in the Capstone Guidebook available from your faculty advisor)
CSCI794 - Research and design a project approve by advisor that furthers the knowledge or has a practical application to the computer science field. This is a two-semester course sequence. The student will register for this course for 2 consecutive semesters (3 credits each semester).
CSCI798 - Research topic in computer science selected by the student and approved by thesis advisor. Students will learn methods for reading technical papers, selecting research topics, devising research questions, reviewing current literature and proposal writings. This is a two-semester course sequence. The student will register for this course for 2 consecutive semesters (3 credits each semester).
This course will look at algorithms and concepts that are popular in the artificial intelligence field. Topics covered may include knowledge representation, constraint satisfaction problems, classical search, adversarial search, probabilistic reasoning, reinforcement learning, and robotics. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees.
This course will look at the algorithms and concepts that are popular in the fields of data mining and machine learning. Topics covered may include deep learning, convolutional neural networks, linear and nonlinear models for classification, kernel methods, support vector machines and dimensionality reduction techniques. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees.
This course will look at current research progress and trends in the Computer Vision field. Topics covered may include scene analysis, object detection and tracking, segmentation, texture and texture based recognition, 2D and 3D object description, and biologically inspired recognition schemes. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees.
This course takes a close look at software as a mechanism for attack, as a tool for protecting resources, and as a resource to be defended. Topics covered include the software design process; choices of programming languages, operating systems, databases and distributed object platforms for building secure systems; common software vulnerabilities, such as buffer overflows and race conditions; auditing software; proving properties of software; software and data watermarking; code obfuscation; tamper resistant software; and the benefits of open and closed source development. Students will demonstrate their ability to produce defect free code from well-known classes of vulnerabilities, including but not limited to design errors, implementation errors, timing errors, and trust. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees.
This course takes a close look at software as a mechanism for attack, as a tool for protecting resources, and as a resource to be defended. Topics covered include the software design process; choices of programming languages, operating systems, databases and distributed object platforms for building secure systems; common software vulnerabilities, such as buffer overflows and race conditions; auditing software; proving properties of software; software and data watermarking; code obfuscation; tamper resistant software; and the benefits of open and closed source development. Students will demonstrate their ability to produce defect free code from well-known classes of vulnerabilities, including but not limited to design errors, implementation errors, timing errors, and trust. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees.
This course provides students with real-world ethical issues facing public and private institutions involving privacy, data integrity, authentication, and internal malicious activity. Professional decision-making requires a thorough understanding and respect for intellectual property, corporate governance, and legal restrictions and regulations. This class will give students the framework to make legal, ethical decisions in their careers. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees.
Prerequisite(s): IAAS600
This course analyzes malware analysis tools and techniques in depth. This training has helped forensic investigators, incident responders, security engineers, and IT administrators acquire the practical skills to examine malicious programs that target and infect Windows systems. Understanding the capabilities of malware is critical to an organization’s ability to derive threat intelligence, respond to information security incidents, and fortify defenses. This course builds a strong foundation for reverse-engineering malicious software using a variety of system and network monitoring utilities, a disassembler, a debugger, and other tools useful for turning malware inside-out. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees.
This course will provide the framework for the techniques and tools used for the extraction of information from digital equipment. Computer forensic tools will be used to gain a thorough understanding of the processes and techniques used in acquiring information and evidence. Topics include federal guidelines for search and seizures, investigating network intrusions, software forensics, and audit logs. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees.
Prerequisite(s): IAAS715