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• DATS 210: Intro to Data Visualization

  3.00 Credits

  Commonwealth University of Pennsylvania

  
  Covers basic concepts of data visualization. Explores the issues and problems in designing and creating graphical representation of data. Topics include fundamentals of visualization and the practice of communicating with data. Focus is on visual encoding and presenting to communicate the data features. The course is intended for students studying data science, physical science or social science. Prerequisite:    CMSC115 OR CMSC130
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• DATS 310: Databases for Big Data

  3.00 Credits

  Commonwealth University of Pennsylvania

  
  Continues the material of CS150, Principles of Database Design. Students learn advanced topics in SQL programming. The course also covers basic concepts, practices, and challenges of big data and distributed analytics computing. Topics include SQL stored procedures and functions, creating triggers and handling exceptions in SQL, Hadoop, MapReduce, related software, and enhanced approaches such as Spark and big data machine learning. The course is intended for students studying data science, computer science, applied computer science, mathematics or statistics. Prerequisite:    CMSC150
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• DATS 320: Data Mining

  3.00 Credits

  Commonwealth University of Pennsylvania

  
  Presents the concepts and issues involved in data mining and students learn how to apply current data mining software for tree-structured data analysis to real-world problems. Prerequisite:    CMSC% AND STAT%
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• DATS 410: Machine Learning

  3.00 Credits

  Commonwealth University of Pennsylvania

  
  Introduces modern machine learning. Machine learning is an active and growing field that is the basis of modern data mining and big data techniques. The course aims at the balance of the theoretical versus practical spectrum. The course covers the concepts behind several machine learning algorithms without going deeply into the mathematics. Students will gain practical experience applying machine learning using Python and related modules. Applications include pattern recognition and artificial intelligence, making the course valuable to students interested in data science, engineering, and intelligent agent applications. Prerequisite:    CMSC130 AND STAT141 OR DATS110 OR STAT241
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• DATS 420: Advanced Data Science

  3.00 Credits

  Commonwealth University of Pennsylvania

  
  Presents Data Science techniques that allow data scientists to successfully complete projects to draw conclusions from big datasets. Students complete a project that starts with "data wrangling" (collecting, cleaning and organizing data). They use techniques learned in the prerequisite classes (Data Visualization, Machine Learning and Databases for Big Data or Advanced Python) to complete the project. The project culminates in a final report and presentation. Prerequisite:    DATS410
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• DGFR 121: Digital Forensics File Sys 1

  3.00 Credits

  Commonwealth University of Pennsylvania

  
  Introduces basic computer forensic methodology. Analysis of File Allocation Table (FAT)file systems, particularly the FAT 32 file system with an emphasis on forensic information from metadata, slack space, and unallocated space. Examination of various Windowsrartifacts using appropriate software.
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• DGFR 122: Digital Forensics File Sys 2

  3.00 Credits

  Commonwealth University of Pennsylvania

  
  Analyzes the NTFS file system in detail with an emphasis on forensic information from metadata, slack space, and unallocated space. Examination of various Windowsr artifacts using appropriate software. Prerequisite:    DGFR121 OR DFC121
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• DGFR 219: Intro to Linux for Dig Forensi

  3.00 Credits

  Commonwealth University of Pennsylvania

  
  Introduces the Linux and related operating systems, emphasizing Linux commands, particularly those useful for digital forensics and security. Basic Linux file systems are examined.
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• DGFR 257: Secure Sys Design & Admin

  3.00 Credits

  Commonwealth University of Pennsylvania

  
  Presents security elements as they apply to systems design, operating system installation and configuration, network hardware devices, and hardware reverse engineering. This is a comprehensive study in security design and implementation.
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• DGFR 275: Intro to Computer Networks

  3.00 Credits

  Commonwealth University of Pennsylvania

  
  Presents a survey of computer network elements. Course focuses on low-level and applied concepts and issues. Local area networks are emphasized; internetworking issues such as routing are also covered. Hands-on activities include: packet sniffing and "wire-level" network traffic, constructing an Ethernet cable, and configuring a LAN. Prerequisite:    DGFR122 OR CMSC130 OR CS122 OR DFC122
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