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Faiz Adegbenro

Faiz Adegbenro

Aspiring AI Trainer / Data Annotator (Self-Initiated Learning & Practice)

NIGERIA flag
Lagos, Nigeria
$14.00/hrIntermediateOtherCVAT

Key Skills

Software

Other
CVATCVAT

Top Subject Matter

Language analysis
sentiment analysis
content categorization

Top Data Types

TextText
ImageImage
VideoVideo

Top Task Types

Classification
Point Key Point

Freelancer Overview

Aspiring AI Trainer / Data Annotator (Self-Initiated Learning & Practice). Core strengths include Other. Education includes Bachelor of Arts, University of Abuja (2025). AI-training focus includes data types such as Text and labeling workflows including Classification.

IntermediateEnglishYoruba

Labeling Experience

Aspiring AI Trainer / Data Annotator (Self-Initiated Learning & Practice)

OtherTextClassification
This role involves hands-on practice in data annotation, focusing on text classification and sentiment analysis. The main responsibilities include following annotation guidelines and ensuring the quality of labeled datasets. Tasks emphasize linguistic accuracy and the application of literary analysis skills. • Practiced various text annotation tasks such as sentiment classification, tagging, and thematic labeling. • Applied language expertise to improve accuracy in data labeling activities. • Developed proficiency in following structured annotation guidelines and standards. • Became familiar with annotation tool workflows relevant to natural language projects.

This role involves hands-on practice in data annotation, focusing on text classification and sentiment analysis. The main responsibilities include following annotation guidelines and ensuring the quality of labeled datasets. Tasks emphasize linguistic accuracy and the application of literary analysis skills. • Practiced various text annotation tasks such as sentiment classification, tagging, and thematic labeling. • Applied language expertise to improve accuracy in data labeling activities. • Developed proficiency in following structured annotation guidelines and standards. • Became familiar with annotation tool workflows relevant to natural language projects.

2025 - Present

Content Categorization Project

OtherTextClassification
During this project, written content was organized and tagged based on identified themes and topics. The effort focused on increasing classification accuracy and ensuring labeled data adhered to specified guidelines. Analysis and classification were performed using critical reading and interpretation skills. • Tagged written content according to themes and topically-relevant categories. • Ensured classification quality through adherence to written guidelines. • Applied detail-oriented analysis for more precise labeling results. • Supported dataset preparation for thematic and topic classification use cases.

During this project, written content was organized and tagged based on identified themes and topics. The effort focused on increasing classification accuracy and ensuring labeled data adhered to specified guidelines. Analysis and classification were performed using critical reading and interpretation skills. • Tagged written content according to themes and topically-relevant categories. • Ensured classification quality through adherence to written guidelines. • Applied detail-oriented analysis for more precise labeling results. • Supported dataset preparation for thematic and topic classification use cases.

Not specified

Text Annotation & Sentiment Analysis Project

OtherTextClassification
In this project, various text data samples were labeled and categorized into sentiment classes. The primary objective was to deliver consistent and accurate sentiment annotation for high-quality datasets. Critical reading and interpretive skills were used to enhance annotation outcomes. • Labeled and categorized text data into positive, negative, and neutral sentiment classes. • Maintained consistency and linguistic attention to detail throughout the process. • Improved overall annotation quality through analysis and guideline adherence. • Contributed to machine learning dataset creation for sentiment tasks.

In this project, various text data samples were labeled and categorized into sentiment classes. The primary objective was to deliver consistent and accurate sentiment annotation for high-quality datasets. Critical reading and interpretive skills were used to enhance annotation outcomes. • Labeled and categorized text data into positive, negative, and neutral sentiment classes. • Maintained consistency and linguistic attention to detail throughout the process. • Improved overall annotation quality through analysis and guideline adherence. • Contributed to machine learning dataset creation for sentiment tasks.

Not specified

Education

U

University of Abuja

Bachelor of Arts, English and Literary Studies

Bachelor of Arts
2025 - 2025

Work History

E

excellent homes and investment

Real estate consultant

lagos
2024 - 2025