Aneke C.

Key Skills

Software

Other

Mindrift

Top Subject Matter

GenAI prompt engineering and NLP

Technology – Software Development & IT Services

Healthcare – Medical Records & Patient Data

Top Data Types

Computer Code Programming

Text

Audio

Top Task Types

Classification

Prompt + Response Writing (SFT)

Entity (NER) Classification

Freelancer Overview

Prompt Engineering (LLM) projects. Core strengths include Other. Education includes Machine Learning Specialization, Coursera (Andrew Ng) (2026) and Python for Everybody Certificate, University of Michigan (2026). AI-training focus includes data types such as Text and labeling workflows including Prompt + Response Writing (SFT) and Entity (NER) Classification.

Labeling Experience

Data Preparation & Quality Assurance for ML Projects

DocumentClassification

Managed data preparation and quality assurance for 15+ machine learning projects across healthcare, education, and social media domains. Project scope included: - Cleaning raw datasets (handling missing values, removing duplicates, standardizing formats) - Data labeling for classification tasks (malignant/benign, survived/died, churn/no churn) - Feature engineering to improve model performance - Train/validation/test splitting with stratification - Quality assurance through cross-validation and error analysis Dataset sizes ranged from 500 to 50,000 rows. All work was performed with careful attention to data quality, consistency, and reproducibility. Projects are documented on GitHub with clear README files and code comments.

2026 - Present

YouTube Comments sentiment analysis project

OtherTextEntity (NER) Classification

Performed NLP classification work on unstructured text data such as YouTube comments, focusing on sentiment-related outputs. Used machine learning approaches to convert textual inputs into labeled sentiment categories. Treated the resulting sentiment categories as model targets for supervised training. • Sentiment analysis on YouTube comments • Text preprocessing and feature extraction (implied) • Supervised classification over labeled targets • Model training and validation on text outcomes

2026

Prompt Engineering (LLM) projects

OtherTextPrompt + Response Writing (SFT)

Developed GenAI prompting workflows for LLMs, including zero-shot and few-shot prompting with chain-of-thought style instructions. Built prompt-engineering experiments to drive sentiment and text understanding tasks from comment-like datasets. Applied prompt design as part of AI training-style iterations using code-based experimentation. • Zero-shot and few-shot prompt formulation • Chain-of-thought prompting experiments • LLM prompt workflows for NLP tasks • Iterative evaluation of prompt effectiveness

2026

Education

Work History