A Peek into the Online Master's Curriculum

Project-based learning is an integral part of many graduate programs. Projects often mirror real-world scenarios to better prepare students for careers or push students to practice their skills in creative ways. But we were curious how these projects translated in an online space, where students aren’t necessarily interacting with their peers or faculty face-to-face. We spoke with two online master’s students to learn more about their favorite projects they completed as part of their programs.

Derik Henriksen, an online MSCS student, said one of his favorite projects was a Capture the Flag game he completed in his cybersecurity course with Associate Teaching Professor Ming Chow.“The thing that's great about the Capture the Flag challenge is that it requires you to be on a team with three or four other people. It's super collaborative,ˮ notes Henriksen. These projects are an important part of the curriculum, as they encourage students to practice new skills while applying their learning in innovative ways. “In all my courses, you learn by doing,ˮ says Chow. 

Hendriksen notes the Capture the Flag game in Chowʼs Introduction to Cybersecurity class “gives you a ton of hands-on experience using the skills you'll need to flex when you're working in cybersecurity.ˮ This project-based design is an intentional aspect of the online programs. As Marty Allen, Teaching Professor and Director of Online Programs, explains, “We're not asking them to break new scientific ground in their projects. They are building skills they can take back to their workplace."

Online MSDS student Lanie Kropp told us that she really enjoyed her capstone project for her Transfer Learning and Medical Imaging course. She shared, “I really liked my final project, mostly because the project's framing was to pick a problem that interests you. This was great for our class because there was such a vast range of interests.” For her project, Kropp sought to identify medical data sets robust enough to train machine learning models within cost and privacy constraints. These models help identify patterns and make predictions that can significantly improve healthcare effectiveness and efficiency.

Kroppʼs approach employed transfer learning, which leverages knowledge from one dataset to inform another. She trained a model on a massive generic image data set with images of dogs, cats, and trees, and transferred that knowledge to X-ray, MRI, and ultrasound images. She also explored transfer learning between medical imaging domains, where well-labeled data from one image type, such as ultrasound, could be used to train models for another image type, like X- rays. "I think it's amazing because it's natural for humans to apply their existing knowledge to new problems,ˮ she explains, “but getting computers to do it is a bit new and exciting."

Group work and project-based learning are an integral part of the master’s curriculum, regardless of modality of learning, and are often students’ favorite parts of the class. These projects give students the opportunity to create something tangible they can add to their portfolio and allow them to apply what they’re learning to their current jobs. From games that teach industry-relevant skills to projects that develop knowledge applicable to the workplace, these projects prepare students for real-world challenges and help them practice skills they’ll continue to use long after they graduate.