Penn’s MSE-AI Online Program: Innovation in AI Education

Please note that recordings of past webinars may contain outdated information. Please see our admissions pages to find the most up-to-date information for application requirements, current tuition, fees, and deadlines.

“AI has an amazingly rich history going back more than 50 years,” noted Professor Chris Callison-Burch during Penn Engineering Online’s January 30, 2025 webinar showcasing the online Master of Science in Engineering in Artificial Intelligence (MSE-AI Online) degree program. “What’s happening now with large language models has really engaged everyone’s imagination.”

Designed for the AI Revolution

Unlike many graduate programs that promise AI expertise, Penn’s MSE-AI Online program specifically targets computer science or computer engineering bachelor’s degree holders seeking to deepen their skills with a focused AI curriculum. This approach allows the curriculum to dive immediately into advanced topics rather than covering basic programming concepts.

“We want to help you pivot into a career in AI within the tech sector,” explained Callison-Burch. The program equips students with three essential pillars of knowledge and skills:

✸ Mathematical foundations of machine learning
✸ Algorithmic and machine learning foundations of AI
✸ Ethical implications of artificial intelligence

The timing for such specialized training couldn’t be better. “It’s not just giant tech companies that are using the technology,” Callison-Burch emphasized. “Every other company can potentially benefit from integration of AI technology into their own workflow.” Graduates will be positioned to lead this integration across industries, whether at established firms or startups. “Our hope is that by the end of your degree, you’ll be able to be a really excellent machine learning ops, AI ops, or LLM ops [engineer], able to benefit any company that wants to integrate AI into their tech stack—or you’ll be able to take advantage of what you’ve learned and start your own company.”

Curriculum Highlights

The program’s seven core courses form a comprehensive curriculum that explores the mathematical, computational and algorithmic foundations of artificial intelligence:

❶ Artificial Intelligence (CIS 5210):
A survey course covering search algorithms, machine learning, probabilistic reasoning, and knowledge representation

❷ Natural Language Processing (CIS 5300):
Explores generative models like GPT and other language technologies

❸ Machine Learning for Data Science (ESE 5410):
Core techniques for pattern recognition and prediction

❹ Statistics for Data Science (ESE 5420):
Statistical foundations essential for AI development

❺ Deep Learning (ESE 5460):
Mathematical approaches to neural network design and implementation

❻ Internet and Web Systems (CIS 5550):
Modern web architectures with AI integration

❼ Technology Ethics and Legal Landscape (EAS 5240):
Co-developed with Penn Law to address ethical and legal considerations

The program also includes two technical electives and one free elective, allowing students to tailor their experience and skill set to their personal and professional goals. A newly developed AI Practicum offers portfolio-building opportunities through team-based projects.

Learning Experience Reimagined

Associate Director of Admissions Jacquie Panto emphasized the program’s flexibility: “There’s nothing that you really ever have to log into (at a specific time), which makes this very unique and extremely flexible.”

While deadlines maintain structure, students control when they engage with the material. Course content is professionally produced, with lecture videos broken into digestible segments. 

This intentional design and production addresses concerns Callison-Burch himself expressed when contemplating the online format. “I worried when we were first designing this that having online students would mean I didn’t actually get a chance to engage with them,” he admitted. Instead, weekly professor office hours have proven to foster engagement and be as impactful as in-person teaching moments, as he explained: “Last night, I had an hour-long discussion with students about DeepSeek’s R1 model that’s really rattled Wall Street—relating it back to course materials. That was really fun.”

Community and Connections

The MSE-AI Online program fosters connection through:

• Course-specific Slack channels
• Geographic Slack channels that often lead to in-person study groups
• Weekly seminars with distinguished researchers and speakers, hosted by the School of Engineering and Applied Sciences (SEAS)
• Career networking events
• Personal academic advising
• Annual on-campus events like Fall Fest and commencement
• Access to peer support through Teaching Assistants, mentors and coaches

“Many students come back and become teaching assistants,” noted Callison-Burch. “I get a chance to continue working with students after the class ends—that’s one of my favorite aspects.”

Pathway for Non-CS Professionals

For those without a computer science background who are interested in pursuing an AI degree, Penn Engineering Online offers a dual degree option. Students can complete the online Master of Computer and Information Technology (MCIT Online) program and then apply to the MSE-AI Online Dual Degree program, with four courses counting toward both degrees. Students hoping to complete a dual degree should communicate this with their academic advisor as early as possible to ensure the correct courses are taken. 

For those interested in applying to the MSE-AI Online degree program, Penn Engineering Online offers two application deadlines per admission cycle (early and regular). For more information, visit the MSE-AI Online admissions page or the Penn Engineering Online YouTube channel to explore recordings of past webinars featuring students, alumni, and faculty.

Key Questions from the Webinar

Next Steps