Moe Sarraf
Developer and designer.
As a Computer Science student deeply engaged with Data Science, AI, and Full-Stack Development, I am driven by a passion to blend creativity and technology. My portfolio, featuring diverse projects such as an interactive React mini-game and an innovative NBA MVP prediction model, is a testament to my commitment to crafting engaging user experiences and leveraging the power of data-driven insights.
Skills
I bring a diverse skill set to the table, encompassing brand design , programming , and education . My expertise lies not only in creating visually appealing designs and efficient code but also in imparting this knowledge through teaching.
FrameWorks
My technical proficiency is anchored in a variety of frameworks that enhance the development process
React
Next.js
Figma
Firebase
Material-UI, Tailwind, BootsTrap
Libraries
I leverage powerful libraries to process data, create machine learning models, and visualize results
Pandas
NumPy
TensorFlow
sci-kitlearn, matplotlib
matplotlib
Programming Languages
Proficient in multiple programming languages, enabling versatility across various projects
C/C++
Python
SQL
Java
HTML/CSS/JavaScript
Portofolio
As a dedicated Computer Science student at Wilfrid Laurier University and an experienced IT Systems and Automation Specialist at Caseware, I, Moe Sarraf, have developed a unique blend of skills in Data Science, AI, and Full-Stack Development. My portfolio showcases diverse projects, such as an NBA MVP prediction model where I harnessed data analytics and machine learning, and a React-based mini-game that demonstrates my proficiency in creating dynamic, user-focused applications. These projects reflect not just my technical acumen but also my passion for blending creativity with functionality, offering a glimpse into my journey of continuous learning and innovation in the ever-evolving tech landscape.
