AI Data Preparation and Annotation (Academic)
I practiced artificial intelligence training workflows by participating in data collection, cleaning, annotation, prompt testing, and output evaluation as part of my university studies. These activities included preparing and refining datasets for AI tasks, labeling data according to project specifications, and evaluating model outputs in iterative cycles. Leveraged AI tools such as ChatGPT, Gemini, and Claude to improve the efficiency and accuracy of the training and annotation processes. • Collected and cleaned text data to create usable datasets • Annotated data with relevant labels for AI training • Conducted prompt engineering and prompt-based testing • Evaluated AI-generated outputs and provided structured feedback