Joseph I.

Key Skills

Software

Other

Top Subject Matter

Healthcare - Medical Records & Patient Data

Finance - Risk Analysis & Fraud Detection

E-commerce - Product Categorization and Customer Support

Top Data Types

Computer Code Programming

Top Task Types

Diagnosis

Question Answering

Text Summarization

Freelancer Overview

Machine Learning thesis: Hepatitis B prediction and early detection model (Computer Engineering, University of Uyo). Brings 2+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Other. Education includes Bachelor of Engineering, University of Uyo (2024) and Certification in Data Analysis, Coursera (2025). AI-training focus includes data types such as Medical, DICOM, and Computer Code and labeling workflows including Diagnosis, Computer Programming, and Coding.

Labeling Experience

Internship tutor (Python Programming Language and Introduction to Data Science and Analysis) at Netisens ICT

Other

Provided tutoring support in Python programming and introductory data science and analysis. Guided a class of over 50 students through learning fundamentals that support downstream data preparation and analytic workflows. Supported learner understanding through instruction and practical exercises. • Tutored a class of 50+ students in Python programming concepts • Delivered instruction for Introduction to Data Science and Analysis topics • Reinforced analytical thinking and programming practice for data work • Helped students build skills needed for working with datasets in analysis contexts

2024 - 2024

Machine Learning thesis: Hepatitis B prediction and early detection model (Computer Engineering, University of Uyo)

OtherDiagnosis

Developed a machine learning model thesis focused on prediction and early detection of Hepatitis B using collected and preprocessed data. Conducted data cleaning, preprocessing, and exploratory data analysis to identify patterns, correlations, and disease risk factors. Trained and evaluated multiple classification algorithms and interpreted model outputs to support early diagnosis and decision-making. • Cleaned and preprocessed dataset using Python (Pandas, NumPy) to improve accuracy and reliability • Performed EDA to extract key patterns and correlations related to Hepatitis B • Implemented and trained classification models including Naive Bayes, SVM, KNN, Decision Tree, Random Forest, Gradient Boosting, Extra Trees, Logistic Regression, AdaBoost • Evaluated performance using accuracy, precision, recall, and F1-score metrics, and visualized results with Matplotlib/Seaborn

2018 - 2024

Education

Work History