How MIT xPRO’s generative AI course bridges the gap between learning and application
Explore MIT xPRO’s multi-layered approach to applied learning.
By MIT xPRO
At MIT, education isn’t just about learning — it’s about translating knowledge into action and innovation. The Institute’s motto, mens et manus (Latin for mind and hand), reflects a commitment to bridging theory and practice.
This philosophy is at the heart of MIT xPRO, where courses are designed around the primary goal of making learning immediately useful. “If you’re just learning all about theory and you don’t know how to actually apply it, it’s really not going to serve you in the real world,” says Luke Hobson, assistant director of instructional design at MIT. “Especially for courses focused on professional development, application is absolutely crucial.”
MIT xPRO’s newest course, Driving Innovation with Generative AI, brings this approach to life, allowing learners to experiment, build, and solve real problems using AI.
“Too often, online education leaves learners wondering, ‘Why am I learning this? How will this actually help me?’ I remember sitting in academic courses where the answer was always, ‘You’ll figure it out someday.’ That’s not good enough,” says Hobson. “If you’re a professional investing time in learning a new skill, you need to know how to use it now — not six months from now.”
The generative AI course was structured around this sense of urgency.
A multi-layered approach to applied learning
Unlike the typical read-and-quiz format of many online learning programs, MIT xPRO takes a dynamic approach to learning.
“For so much of online education, it’s just, ‘Do this reading, take this quiz,’ and that’s called a course. But that’s not a good course,” Hobson explains. “We use a variety of learning assessments and activities to make sure people are getting the most out of the experience.”
Scenario-based learning: Learners face hypothetical challenges where they must think critically, make decisions, and navigate complex situations relevant to their industries.
Case study analysis: Learners uncover key insights that help them recognize patterns and apply lessons directly to their work.
Peer review: Learners gain valuable perspectives from professionals in different industries, enriching their understanding of generative AI applications beyond their own fields.
But perhaps the most valuable element of the course is the integration of hands-on projects.
Generative AI application in real-world scenarios
The generative AI course is designed for professionals looking to solve real problems in their industries. To do that, learners must have the opportunity to experiment with tools, tackle industry-relevant challenges, and create AI-driven solutions. “There are a ton of projects in the course,” says Hobson.
For instance, one learner from a marketing background explored how generative AI could help with commercial production. She experimented with generative tools to create video, music, and voiceovers, building a workflow she could bring back to her company.
Through the completion of the course’s many projects, learners get the chance to ask questions and receive feedback every step of the way.
Standout assignment: Creating a custom GPT
One of the standout assignments is creating a custom GPT — an AI-powered assistant tailored to each learner’s industry and, in many cases, their specific role.
“For a lot of people, this is their first time building a custom GPT,” says Hobson. He explains that learners are instructed to think of the custom GPT as a sidekick that will make their job easier.
The results are often immediately applicable. For example, a learner who was struggling with contract documentation at her job developed a tool to assist with drafting legal documents. She then took the tool back to her workplace and put it to use.
Another learner, Tiyash Bandyopadhyay, created a Strategic Matrix Consultant GPT designed to help professionals “[make] high-stakes decisions against competing priorities in the face of information overload.”
Exploring the ethical and practical challenges of generative AI
Understanding generative AI isn’t just about knowing what it can do but also recognizing its limitations and ethical implications.
“We provide a realistic look at what generative AI can’t do,” Hobson explains. “DALL-E, for instance, struggles with generating certain details, like human fingers or realistic license plates. That might seem small, but when you think about the bigger picture — like AI-generated misinformation or deepfakes — it’s clear that it’s a big issue.”
An eye-opening exercise involves showing learners a mix of authentic and AI-generated images of faces and asking them which ones are real. “No one gets it right,” says Hobson.”
Exposure to a wide range of AI tools
To complete hands-on projects, learners engage with a variety of AI tools, selecting the most appropriate ones for each assignment. Rather than prescribing a single tool, MIT xPRO allows learners to explore and compare different options, reinforcing their ability to critically assess and apply AI in real-world contexts.
Tools learners might use include the following:
- Large language models (LLMs): ChatGPT, Gemini, Claude, Llama
- Image generation: DALL-E, Stable Diffusion, Dream Studio
- Music and audio: Suno, MusicLM
- Video and animation: Runway, Sora
- Research and knowledge organization: NotebookLM
The power of collaboration in online learning
Another major differentiator of MIT xPRO courses is the focus on collaboration and networking — a crucial element often missing in online learning programs. “In the real world, you work with a team. You don’t just sit in a silo,” says Hobson. Yet, in online learning courses, that’s exactly what often happens.
Whether it’s integrating AI into a business strategy, optimizing workflows, or making informed decisions, success depends on collaborating with colleagues, stakeholders, and industry peers.
To foster this essential skill, the generative AI course begins with a networking session where learners meet in small breakout groups, introduce themselves, and discuss their industries and goals. This structure ensures that from day one, learners are engaging in the kind of teamwork and knowledge-sharing that mirrors how AI is applied successfully in real-world environments.
A generative AI course for any industry
The generative AI course is designed to be accessible to learners from diverse backgrounds, including IT, education, healthcare, finance, data analytics, government agencies, and journalism. Prior experience with AI or coding is not required.
For those who want to explore AI before the course begins, Hobson recommends Ethan Mollick’s Co-Intelligence as an approachable guide to AI’s role in business and society. The MIT Technology Review also provides frequent updates on AI developments, many of which are incorporated into the course.
Shaping the future of generative AI education
MIT xPRO’s commitment to bridging the gap between learning and application is ongoing. With AI evolving rapidly, the course continuously adapts based on learner feedback.
“We actually use the feedback learners give us,” says Hobson. When some participants requested a deeper dive into the topic of coding, MIT xPRO introduced separate learning tracks — one for learners with prior coding knowledge and another for complete beginners. The goal is to make sure that every learner, regardless of background, gets the most value out of the course.
Hobson reveals that MIT xPRO is also in the process of adding more generative AI courses, including one on deploying generative AI to implement business strategy. “We keep hearing from professionals who want to understand how to incorporate AI into their organization’s strategic vision,” says Hobson. “So we’re developing a brand new course designed to guide learners through that process.”
As AI continues to evolve, staying ahead means not only learning about innovative tools but also actively applying them. Whether you’re looking to integrate generative AI into your business strategy, optimize workflows, or explore cutting-edge applications, MIT xPRO’s generative AI course is designed to help you turn knowledge into action. Enroll today to get started!
Part of MIT Open Learning, MIT xPRO provides professional development opportunities to a global audience via online courses and blended programs.
