Student Learning Outcomes

 

 

 

PhD in Computer Science and Software Engineering

The vision of the Doctor of Philosophy in Computer Science and Software Engineering (PhD-CSSE) program at Auburn University is to develop doctoral students’ research skills in cutting-edge computer science and software engineering disciplines. We cater to doctoral students with strong research skills and outstanding teaching skills and in computer science and software engineering. There are four student learning outcomes (SLO 1-4) defined to implement our PhD-CSSE program vision.

  • SLO 1: Students will demonstrate mastery with in-depth knowledge in algorithms, operating systems, and architecture.
  • SLO 2: Students will be able to develop and evaluate software systems to meet desired requirements.
  • SLO 3: Students will perform cutting-edge research in at least one area of specialty.
  • SLO 4: Students will communicate concepts and results to technical audiences in the format of conference/journal papers as well as oral presentations.

 

Master of Science in Computer Science and Softare Engineering

The vision of the Master of Science in Computer Science and Software Engineering (MS-CSSE) program at Auburn University is to offer a unique opportunity for Master’s students to develop cutting-edge and in-depth knowledge of computer science and software engineering disciplines. We cater to Master’s students with an outstanding aptitude and strong analytic skills for software design and development. There are four student learning outcomes (SLO 1-4) defined to implement our MS-CSSE program vision.

  • SLO 1: Students will demonstrate proficiency of core knowledge in algorithms, computer architecture, and operating systems.
  • SLO 2: Students will be able to implement and test software solutions to problems.
  • SLO 3: Students will apply reasoning and technical skills to solve problems in at least one area of research.
  • SLO 4: Students will effectively communicate with non-technical and technical audiences during software lifecycles.

 

Master of Science in Cybersecurity Engineering

This graduate program prepares students for analyzing, developing, investigating, protecting, and defending the cyber ecosystem of organizations. As such, it focuses on the engineering and technical aspects of cybersecurity. The degree is designed to appeal to practitioners as well as research scholars through the inclusion of capstone experience. There are six student learning outcomes (SLOs 1-6) defined to implement our MS-CYBE program vision.

  • SLO 1: Students know prevalent cybersecurity threats and canonical defenses.
  • SLO 2: Students have the ability to identify, assess, and defend against cybersecurity threats; develop suitably protective and resilient network and software mechanisms; and detect, triage, and mitigate cybersecurity breaches.
  • SLO 3: Students are versed in techniques for gathering and preserving digital forensic evidence relating to a cyber event.
  • SLO 4: Students possess a graduate level knowledge of algorithms, operating systems, and computer architectures, and have the ability to leverage this knowledge for a deeper contextualized understanding of cybersecurity.
  • SLO 5: Students communicate cybersecurity issues effectively to both technical and non-technical audiences.
  • SLO 6: Students have the ability to apply their cybersecurity capabilities in an integrated manner to address specific cybersecurity problems.

Master of Science in Data Science and Engineering

This graduate program prepares students to pursue careers in data science and engineering, where valuable insights are derived from massive amounts of raw data. Our high‐quality curriculum offers an excellent balance between theory and application, equipping students with foundational skills and state‐of‐the‐art technologies related to the next generation of big data applications. Students will be able to complete this on‐campus graduate program in one to two years. This program blends graduate‐level courses in core topics like data mining, machine learning, and statistical learning. The program also offers a wide variety of electives in addition to a required capstone experience, in which students apply their knowledge and skills to a real‐world application scenario. The MS-DSE program encompasses four student learning outcomes (SLO 1-4).

  • SLO 1: Students will incorporate the theoretical math and statistical principles to design and implement solutions to solve data analytics problems.
  • SLO 2: Students will utilize practical computing technologies to design and implement data-driven solutions.
  • SLO 3: Students will apply data science and engineering methods to at least one domain of real-world applications.
  • SLO 4: Students will deliver written and oral presentations to non-technical and technical audiences during the design and implementation phases of data science and engineering projects.

 

Graduate Certificate in Cybersecurity Engineering

This graduate certificate program has three student learning outcomes (SLO 1-3).

  • SLO 1: Students know prevalent cybersecurity threats and canonical defenses.
  • SLO 2: Students have the ability to identify, assess, and defend against cybersecurity threats; develop suitably protective and resilient network and software mechanisms; and detect, triage, and mitigate cybersecurity breaches.
  • SLO 3: Students are versed in techniques for gathering and preserving digital forensic evidence relating to a cyber event.

 

Document History: Revised on June 26, 2020. Version 1.0 


Last Updated: 6/26/20 1:13 AM