Mohammed R. Awad — AI, Data Analytics and Machine Learning

Portrait of Mohammed R. Awad

Available for remote opportunities

Mohammed R. Awad

Computer Engineering student building machine-learning systems and useful data products.

I am a

Explore projects Download CV

01 — About

Built under pressure,
driven by curiosity.

I'm a Computer Engineering student focused on Intelligent Systems at Al-Aqsa University, based in Gaza, Palestine — and I'm building my way into tech.

My work spans AI, Data Analytics, and Machine Learning. What I enjoy most is turning ideas into real products: AI-powered web apps and tools that actually solve problems. Every project teaches me something new, and that's the part I never get tired of.

My story isn't a straight line. I kept building, studying, and shipping through extremely difficult circumstances — power cuts, unstable internet, and everything that comes with living through a crisis. Those constraints didn't stop the work; they shaped how I work: resourceful, self-taught, and relentless about finishing what I start.

I'm still learning, and I plan to keep going. When things get hard, you adapt; you don't quit. Skills can be taught, but consistency is what carries you through.

Freelance — AI Design Visualization

I run a small freelance service using generative-AI image tools to produce interior-design visualizations for real clients — wedding halls and cafés — turning rough ideas into photorealistic concepts they can act on.

Volunteer — Community Data Organization

During a crisis period I volunteered to organize and structure community data, helping local efforts track needs and resources when it mattered most.

02 — Skills

Tools I think in.

Core strengths

  1. Machine Learning & Analytics

    EDA, preprocessing, classifier comparison, interpretation, and research-driven evaluation.

    Shown in churn prediction and pattern-recognition work ↓

  2. AI Agents & Applied GenAI

    LangChain foundations, Claude API workflows, agent skills, subagents, and responsible AI practice.

    Backed by verified credentials ↓

  3. Web Product Delivery

    Responsive, accessible interfaces built with semantic HTML, modern CSS, and vanilla JavaScript.

    Shown in Gaza Aid and this portfolio ↓

AI & Machine Learning

  • Prompt Engineering
  • Claude API
  • LangChain
  • AI Agents
  • Generative AI
  • Responsible AI
  • scikit-learn
  • Deep Learning

Data & Analytics

  • Python
  • pandas
  • Data Analysis
  • EDA
  • Pattern Recognition
  • MATLAB

Also fluent in

  • Flutter & Dart
  • Java

Tools

  • Git & GitHub
  • VS Code
  • Claude Code
  • Google Colab
  • Cisco Packet Tracer

03 — Projects

Selected work.

  • Featured · Machine Learning

    Bank Customer Churn Prediction

    Problem
    Identify customers at risk of leaving while handling an imbalanced churn class.
    My contribution
    Built the complete notebook workflow, from data quality checks and EDA to model evaluation and interpretation.
    Approach
    Compared Logistic Regression, Random Forest, tuned XGBoost, and an MLP using stratified train, validation, and test splits.
    Result
    0.855 ROC-AUC and 72.5% recall on the held-out test set with tuned XGBoost.
    • Python
    • pandas
    • scikit-learn
    • XGBoost
    View notebook ↗ Source code ↗

  • Featured · Web Product

    Gaza Aid

    Problem
    Make humanitarian resources, reporting, registration, and request-status tools easier to find in one interface.
    My contribution
    Designed and built the complete multi-page experience, including responsive navigation, forms, and Arabic-first content.
    Approach
    Created a lightweight front end with semantic HTML, custom CSS, and vanilla JavaScript, plus PHP form endpoints.
    Result
    5 focused user flows delivered across the home, registration, reporting, status, and contact pages.
    • HTML
    • CSS
    • JavaScript
    • PHP
    Live demo ↗ Code ↗

  • Featured · Research

    Pattern Recognition Research

    Problem
    Understand when feature scaling changes which classifier is the best choice for a pattern-recognition task.
    My contribution
    Framed the research question, compared algorithm sensitivity, and organized the findings into a focused technical report.
    Approach
    Analyzed distance-based, margin-based, probabilistic, tree-based, and neural classifiers through the lens of feature scale.
    Result
    5 classifier families mapped to practical scaling decisions in a documented analytical study.
    • Pattern Recognition
    • Feature Scaling
    • Research
    Read paper ↗ Repository ↗

  • ML Research

    A growing collection of machine-learning work: Python, data science, deep learning, and data-analysis experiments and notes.

    • Python
    • Data Science
    • Deep Learning
    Read paper ↗ Repository ↗

  • IT Company

    Java application modeling an IT company: OOP design, class relationships, collections (ArrayList), and file handling.

    • Java
    • OOP
    • Collections
    • File I/O
    Code ↗

  • Campus Network Design

    Complete campus network in Cisco Packet Tracer: DHCP, RADIUS authentication, and WPA2-Enterprise wireless security.

    • Packet Tracer
    • DHCP
    • RADIUS
    • WPA2-Enterprise
    Topology ↗

  • Library System

    Library management system built in Java with a clean object-oriented structure for books, members, and loans.

    • Java
    • OOP
    Code ↗

  • Control System

    Control-system designs for classic automation scenarios: a traffic-signal controller and a water-pump controller.

    • Automation
    • Control Systems
    Code ↗

04 — Certificates

Proof of the reps.

05 — Contact

Let's build something.

Available for remote internships, junior AI and data roles, selected freelance work, and thoughtful collaborations. Send a message here and I'll reply by email.