- 2026-02-13
- Eduardo Rivera
As part of the collaboration between Universidad de Ingeniería y Tecnología (UTEC) and the MIT–Peru Program, 13 student instructors from the MIT traveled to Lima this January to teach an intensive course in introductory artificial intelligence to 70 local students.
Over the course of the program, MIT instructors delivered lectures, facilitated hands-on coding sessions, and mentored student teams through applied AI projects. The curriculum covered foundational machine learning concepts, data preprocessing, supervised learning methods, and ethical considerations in AI deployment. Students implemented models in Python and worked with real datasets relevant to regional challenges.
The initiative reflects a shared commitment by UTEC and MIT, institutions that have partnered since 2013, to expand access to advanced computing education in Peru, where demand for high-level training in computer science and artificial intelligence continues to outpace supply.
A national need for advanced computing skills
Peru has experienced steady growth in its technology sector; however, structural gaps remain in advanced STEM training. According to the Peruvian publication Economía, digital and computing-related occupations are among the fastest-growing fields in Latin America. Nevertheless, enrollment and graduation rates in computer science and related disciplines remain comparatively low relative to projected workforce demand.
Recent assessments of Peru’s higher education landscape indicate:
- A shortage of faculty specializing in advanced computer science fields such as machine learning, data science, and artificial intelligence.
- Limited access to hands-on, project-based AI coursework outside major metropolitan institutions.
- A widening gap between industry demand for AI competencies and the availability of formally trained graduates.
For emerging economies like Peru, strengthening local capacity in advanced computing is critical to economic competitiveness and inclusive growth.
A collaborative teaching model
The MIT student instructors, many of whom are experienced teaching assistants and researchers in computer science and related disciplines, adapted their course design to the local academic context. Rather than focusing solely on theory, the course emphasized implementation: students built classification models, evaluated performance metrics, and examined real-world deployment constraints.
Throughout the program, instruction was structured around small-group problem solving and iterative feedback. The 70 participating UTEC students worked in teams, applying newly acquired techniques to datasets addressing issues such as computer vision, NLP, resource optimization and pattern recognition.
The collaboration also fostered peer-to-peer exchange. MIT instructors gained insight into Peru’s educational ecosystem and the specific challenges faced by students entering technical fields. UTEC students, in turn, benefited from exposure to pedagogical approaches commonly used at MIT, including active learning, code reviews, and project-based learning.
Building long-term capacity
The MIT–Peru GTL AI program is part of a broader agreement that includes research seed funding for joint projects between faculty and researchers from both universities, as well as internships and academic visits. As such, the GTL AI initiative is designed not as a one-time intervention, but as part of a sustained partnership model with UTEC. By aligning curriculum development, faculty collaboration, and student engagement, the program seeks to support long-term capacity building in artificial intelligence and advanced computing.
As Peru continues to integrate digital technologies across sectors—from finance and healthcare to public administration—initiatives that strengthen foundational AI literacy and advanced technical training will play a critical role. Programs like the UTEC–MIT collaboration demonstrate how international academic partnerships can contribute to developing local expertise while promoting cross-cultural exchange in rapidly evolving technical fields.