Machine Learning Information Technology

YACQUB ISSE SALAH

Parit Raja, Johor • ************@*****.*** • 011******** •

http://linkedin.com/in/yacqub-isse-4b7909237

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EDUCATION

UNIVERSITY TUN HUSSEIN ONN

MALAYSIA (In Progress)

Parit Raja, Johor

Bachelor in Information Technology with Honours

• CGPA: 3.14

Mar 2022 – Jul 2025

RELEVANT COURSEWORK Garowe, Somalia

Database Systems, SQL & Data Structures

PROFESSIONAL EXPERIENCE

Oct 2022 – Mar 2024

Golis Telecommunications - Garowe, Somalia Support Oct 2021 – Jan 2021

• Worked with the IT team to troubleshoot database-related problems and keep operations running smoothly.

• Supported the IT team in daily database operations, including data entry and data recovery.

• Installed and configured computer hardware, including desktops, laptops for small business and individual clients.

• Gained practical experience using SQL and database management tools. LEADERSHIP & ACTIVITIES

SOMALI INTERNATIONAL STUDENT UTHM

Vice-president Parit Raja, Johor

Feb 2023 – Mar 2024

Al- xigma Secondary School

Secretary of finance Garowe, Somalia

May 2020–Mar 2021

CERTIFICATION

Machine learning may 2023

• Supervised and Unsupervised Learning (e.g., Linear Regression, K-Nearest Neighbors, Clustering)

• Model Evaluation and Tuning (e.g., Cross-Validation, Hyperparameter Tuning)

• Libraries: scikit-learn, TensorFlow, Keras, PyTorch Programming Language

Python, SQL,Java

June 2023

Database Management

SQL Server, MySQL

May 2023

Transferable skills Feb 2023

Analytical thinking, attention to detail, teamwork, problem-solving Cisco Certified Network Associate (CCNA) Mar 2025

Projects 2024-2025

• Cancer Detection Using Convolutional Neural Networks (CNN) Developed an image classification model to detect cancer using medical imaging data. Implemented Convolutional Neural Networks (CNNs) to classify images and predict cancer types and stages.Tools used: Python, TensorFlow, Keras, OpenCV.

• Tomato Plant Disease Detection Using Machine Learning Created an image classification model in my final year project to identify diseases in tomato plants using various machine learning algorithms. Applied Random Forest (RF), Support Vector Machine (SVM), and K-Nearest Neighbors (KNN) to classify plant disease images. Tools used: Python, scikit-learn, OpenCV, Pandas, Matplotlib. ADDITIONAL INFORMATION

● Languages: English (Fluent), Somali (Native), Arabic (Fluent)

● Awards: Dean’s List Award (Semester 4) at UTHM

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