Graduates of the Master’s Program in Applied Artificial Intelligence at Universidad de Las Américas are highly competent, enterprising professionals with an international-global vision, capable of leading the technological transformation driven by advances in artificial intelligence worldwide. Similarly, graduates are equipped to leverage the potential of artificial intelligence and translate it into commercial value, solving organizational challenges through the application of machine learning techniques and the implementation of intelligent systems for diverse business purposes.
Furthermore, graduates manage technological, analytical, and human capabilities to foster the development of new organizational competencies grounded in artificial intelligence. Graduates analyze economic, social, and ethical factors relevant to the implementation of AI projects and apply both theoretical and technical knowledge to design strategic and operational solutions within corporate environments. In addition, graduates apply artificial intelligence techniques and employ machine learning methodologies to develop intelligent systems for organizational use.
Ultimately, graduates are expected to lead multidisciplinary teams in both national and international contexts, demonstrating ethical conduct, creativity, proactiveness, innovation, and responsibility. Graduates uphold current legal frameworks and serve the interests of society, contributing to the country's technological development.
Demographic Data - provides information about student enrollment disaggregated by gender and ethnicity, offering insight into the demographic diversity within the program.
Student Completion - provides information about graduation rates and graduation rates disaggregated by gender calculated through the 2021–2022 academic year, based on cohorts of new, first-time students, regardless of enrollment in the program's daytime or evening instructional delivery (if applicable).
All programs utilize the Brightspace platform to collect and assess student work and to compile data and evidence of student achievement. The resulting outcomes and their analysis, which focus on identifying areas for improvement, are presented in the program’s assessment report. In the graphic below, the most recent assessment period for each Program Learning Outcome (PLO) is indicated, along with the percentage representing the level of achievement of the expected performance standard for that PLO, based on the rubric used to evaluate student work.