Training future ML engineers: a project-based course on MLOps
Recently, the proliferation of commercial ML-based services has given rise to new job roles, such as ML engineers. Despite being highly sought-after in the job market, ML engineers are difficult to recruit, possibly due to the lack of specialized academic curricula for this position at universities....
| Autores: | , , |
|---|---|
| Tipo de recurso: | artículo |
| Fecha de publicación: | 2023 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/395116 |
| Acceso en línea: | https://hdl.handle.net/2117/395116 https://dx.doi.org/10.1109/MS.2023.3310768 |
| Access Level: | acceso abierto |
| Palabra clave: | Machine learning -- Study and teaching (Higher) Codes Reproducibility of results Pipelines Surveys Data science Training Software engineering Aprenentatge automàtic -- Ensenyament universitari Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàtic Àrees temàtiques de la UPC::Ensenyament i aprenentatge::Ensenyament universitari |
| Sumario: | Recently, the proliferation of commercial ML-based services has given rise to new job roles, such as ML engineers. Despite being highly sought-after in the job market, ML engineers are difficult to recruit, possibly due to the lack of specialized academic curricula for this position at universities. To address this gap, in the past two years, we have supplemented traditional Computer Science and Data Science university courses with a project-based course on MLOps focused on the fundamental skills required of ML engineers. In this paper, we present an overview of the course by showcasing a couple of sample projects developed by our students. Additionally, we share the lessons learned from offering the course at two different institutions. |
|---|