Future Engineers Join the AI Revolution
Computer engineering students leveraged the knowledge gained in their Large Language Models course by using AI to design innovative solutions.
Large Language Models (LLM)—the powerhouse of generative AI and advanced machine learning models designed for natural language processing—have become essential for aspiring computer engineers striving to keep pace with the rapidly evolving tech landscape.
Demonstrating the School of Engineering’s commitment to an up-to-date curriculum and preparing industry-ready graduates, senior computer engineering students gained firsthand experience through hands-on projects in their LLMs course, which they conceptualized and developed during the Fall ’24 semester.
The projects required the students to develop AI agentic frameworks, offering the students the opportunity to explore a variety of real-life applications, including study assistants, customer support tools, content generation and food and beverage recommendation systems.
In addition to backend integration using software frameworks like LangChain, the students worked on developing frontend user interfaces and dashboards, ensuring their solutions were both practical and user-friendly—all showcased through a fully functional web app.
“Such a comprehensive project development approach is central to modern software development,” said Assistant Professor Samer Saab Jr. “Companies are actively seeking graduates with these specific skills to enhance their AI capabilities,” he added.
One of the projects, Study Buddy, was developed by fourth-year engineering students Jane Daou and Razan Houdaifa (BE ’24) to help students extract key information, summarize content and generate multiple-choice questions from study material.
“Time management is a common challenge for students,” said Houdaifa. “That’s why we wanted to develop a solution that enhances study planning through LLM-based automation.”
“Despite the challenge of fine-tuning our prompting strategy, I became more confident in my ability to refine AI-driven tools for accuracy, usability and scalability,” said Daou.
According to Dr. Saab Jr., the projects highlighted the importance of ethical AI, ensuring that students’ systems generated responsible and accurate results by carefully shaping how the AI interacts with users.
Fourth-year engineering student Elissa Diab found that developing an LLM-powered fitness assistant—capable of generating personalized diet plans, tracking calories and recommending recipes—aligned perfectly with her interest in exploring advanced AI models like ChatGPT and Gemini.
“Beyond the course, I had the opportunity to apply my knowledge in a competitive setting,” said Diab, who went on to participate in the Apgar Smart Academy Challenge coding competition held on January 14 at the LAU Byblos campus. Her innovative design and development of a learning assistant application, using prompt engineering and strategic AI integration, earned her a six-month paid internship at the academy.