About Me

Computer Science graduate from King Saud University, specialized in Cloud Computing and Networking. Experienced managing enterprise networks supporting 5,000+ users during peak periods including Hajj season.

Co-op at Saudi Broadcasting Authority — configured Cisco switches and routers, monitored live infrastructure, and built Python automation scripts that improved operational efficiency.

Strong foundation in networking protocols, virtualization, and cloud platforms. I optimize everything I work on.

Networking Skills
Cisco IOSSwitches & Routers VLANsDNS & DHCP WiresharkGNS3SNMP
Cloud & Virtualization
AWS EC2AWS S3 VPCIAM VMware WorkstationVMware ESXi
Education
King Saud University
B.Sc. Applied Computer Science – Computer Networks · Second Honors
2020 – 2025 · Saudi Arabia
  • Designed and configured network infrastructures: switches, routers, VLANs, DNS, DHCP.
  • Hands-on with VMware, virtual networks, and cloud architectures.
  • Diagnosed and optimized network performance and protocols.
Saudi Arabia Arabic (Native) · English (Professional)

Experience

Saudi Broadcasting Authority (SBA)
Co-op Trainee – Network Support & Operations
January – July 2025 · Saudi Arabia
Key Achievements
  • Ensured uninterrupted network for 5,000+ users during Hajj season.
  • Built Python SNMP automation script, enhancing management efficiency.
  • Resolved critical connectivity issues, reducing network downtime.
Core Responsibilities
  • Configured switches, routers, and access points for security and performance.
  • Monitored and troubleshot network infrastructure for consistent uptime.
  • Collaborated with IT teams on enterprise-wide improvements.
5,000+
Users Supported
6 mo.
Co-op Duration

Courses & Training

Cloud
AWS Solutions Architect – Associate
Misk Skills · December 2025 · 40 hours  ·  Training / Course
EC2, S3, VPC, IAM — scalable, fault-tolerant cloud architecture design on AWS.
Course Certificate
Networking
CCNA 200-301
Abad Network · Nov – Dec 2025 · 60 hours  ·  Training / Course
Network fundamentals, IP connectivity, security, and programmability per Cisco associate standard.
Course Certificate
Programming
Python 101–104
Satr Platform · Basic to Intermediate
Python from basics to intermediate — automation, scripting, and network use cases.

Projects

Graduation Project
Detection & Classification of Bone Fractures
Deep Learning · Neural Networks · Transfer Learning
Deep learning system classifying X-ray fractures via transfer learning — improved medical diagnostic accuracy.
PythonDeep LearningTransfer Learning
Project Summary
Networking Labs
Network Infrastructure Labs
Cisco · VMware · GNS3 · Virtual Environments
Hands-on networking labs covering VLAN segmentation, Inter-VLAN routing, DNS, and DHCP configuration on enterprise-scale simulated environments using Cisco IOS, VMware, and GNS3.
Cisco IOS VLANs Inter-VLAN DNS DHCP VMware GNS3
VLAN Report Inter-VLAN Report DHCP Report DNS Report
AWS Cloud
Cloud Resume Website — This Site
AWS S3 · CloudFront · GitHub Actions · CI/CD
Fully automated cloud-hosted portfolio. Push to GitHub → pipeline runs → site updates globally.
Deployment Pipeline
1
Update CV
Edit HTML or PDF locally
2
Push to GitHub
Commit triggers the workflow
3
GitHub Actions Runs
CI/CD workflow executes automatically
4
Files Upload to S3
Static assets synced to AWS S3
5
CloudFront Cache Invalidates
CDN cache cleared for fresh content
✓
Website Updates Globally
Live via CloudFront edge nodes worldwide
AWS S3CloudFrontGitHub ActionsCI/CD
AI · AWS Serverless
Plant Disease Detection System
SageMaker · Lambda · API Gateway · DynamoDB · EfficientNetB3
Serverless AI system that diagnoses plant leaf diseases from photos with 99.41% accuracy. Farmers upload a leaf image and receive an instant diagnosis with treatment recommendations — fully automated, zero idle cost.
Request Flow
1
User Uploads Leaf Photo
Web app hosted on S3 sends HTTPS POST
2
API Gateway
Routes request to Lambda function
3
Lambda Preprocesses Image
Validates & resizes to 224×224, calls SageMaker
4
SageMaker Serverless Inference
EfficientNetB3 classifies across 38 disease classes
5
Result Logged to DynamoDB
Prediction, confidence & timestamp stored
✓
Diagnosis Returned in ~1–2s
Disease name, status & treatment recommendation
SageMaker Lambda API Gateway DynamoDB EfficientNetB3 99.41% Accuracy
Live Demo