Qasim Mahfoodh

Artificial Intelligence Specialization · Cohort 2026

Optimization of Data Center Siting in Saudi Arabia for Future Energy Mix Planning

Efficient planning is necessary to ensure sustainable energy utilization with the rapid expansion of data centers and the increasing need for a reliable digital infrastructure. This project is intended to optimize the siting of data centers in Saudi Arabia by evaluating suitable locations and evaluating potential energy mix scenarios using the PLEXOS modeling platform. In the first phase of the project, a first PLEXOS model skeleton was developed and the data sets required were collected and organized, including electricity demand, power generation technologies, renewable energy resources and energy mix data. These early results lay the groundwork for future model implementation, scenario analysis and optimization. The project is expected to support informed decisions for the sustainable deployment of data centers aligned with Saudi Vision 2030.

Read the final report (PDF)

Artificial Intelligence Specialization · Cohort 2025

V2N: Deep Learning-Based System for Transforming Educational Videos into Interactive Jupyter Notebooks

YouTube is the world’s top destination for self-learning, yet it lacks the interactive structure needed for real understanding — users watch but rarely implement. Unlike structured courses that combine theory with hands-on practice through lab quizzes and notebooks, YouTube leaves learners passive. This idea proposes an AI-powered system that converts educational YouTube videos into Coursera-style Jupyter notebooks, complete with a summary, visual explanations, and interactive tasks like code completions and problem-solving exercises. By leveraging video and transcript understanding alongside content generation models, the system bridges the gap between passive watching and active learning — turning YouTube into a true learning platform.

Mentor: Salman Khan

Read the final report (PDF)

See it in the program report (PDF)