Turning Software Engineers into AI Engineers
Project Overview
The document outlines an educational initiative at Fontys University of Applied Sciences designed to transition software engineers into AI engineers, addressing the increasing demand for machine learning expertise in software development. It details the ICT & AI program's structure, which merges machine learning concepts with software engineering practices, highlighting the significance of project-based learning and effective data preparation. The program's findings underscore the necessity for students to acquire a comprehensive understanding of both machine learning and software engineering to align with industry requirements. Overall, the initiative aims to equip students with the essential skills to thrive in the evolving technological landscape, ensuring they are well-prepared for the challenges and opportunities presented by generative AI in education and beyond.
Key Applications
ICT & AI program at Fontys UAS
Context: Higher education for software engineering students aiming to specialize in AI and machine learning.
Implementation: The program includes four semesters of applied Software Engineering and two semesters of applied AI, with practical assignments and internships.
Outcomes: Graduates are well-prepared for AI engineering roles, with practical experience in machine learning applications and data handling.
Challenges: Some students expressed a need for more knowledge in testing machine learning applications and topics like unsupervised learning and deployment.
Implementation Barriers
Educational Barriers
Students often lack a strong mathematical background which is traditionally important for understanding machine learning. Additionally, there is limited study material and resources for certain advanced topics like unsupervised learning and deployment of machine learning solutions.
Proposed Solutions: The program focuses on intuitive understanding of machine learning concepts without delving deep into advanced mathematics. Incorporating guest lectures and additional reference materials in later versions of the program.
Project Team
Petra Heck
Researcher
Gerard Schouten
Researcher
Contact Information
For information about the paper, please contact the authors.
Authors: Petra Heck, Gerard Schouten
Source Publication: View Original PaperLink opens in a new window
Project Contact: Dr. Jianhua Yang
LLM Model Version: gpt-4o-mini-2024-07-18
Analysis Provider: Openai