Forage Academy Data Labeling

Get Career Ready

Complete work that simulates life on the job. 3-4 hours and self-paced.

Stand out in your application to Forage Academy. Show us you're a motivated candidate.

Get Career Ready

Complete work that simulates life on the job. 3-4 hours and self-paced.

Stand out in your application to Forage Academy. Show us you're a motivated candidate.

Why complete this job simulation

A risk-free way to experience work on the job with us at Forage Academy. Practice your skills with example tasks and build your confidence to ace your applications.

Self-paced3-4 hoursNo gradesNo assessmentsIntroductory

Welcome to the Forage Data Labeling Simulation!

We're excited to have you join us for an immersive, hands-on journey into the world of modern AI data operations. Whether you're curious about how labeled data powers machine learning or you're eager to test your eye for detail, this program is your launchpad.

Across two engaging tasks, you'll step into the shoes of an entry-level data labeler and then a quality reviewer. You'll apply simple guidelines to short customer-support messages, practice privacy-aware labeling by flagging PII, and learn how small decisions affect model behavior. You'll also review pre-labeled items, make Keep/Fix/Flag calls with brief justifications, and propose targeted improvements to the guidelines, just like real teams do.

Get ready to learn, experiment, and show off your judgment, as you discover what it takes to produce clear, consistent, and ethical labels that make AI work.

Skills you will learn and practice:

Attention to Detail

Data Privacy

Documentation

Analytical Thinking

Feedback Delivery

How it works

key 'simulation.landing.tasksSection.heading (en)' returned an object instead of string.

Intro & Scenario

Meet your team members and learn about your project goals.

Your role

Entry-level Data Labeler on a help center AI project
Apply a small schema: Intent, Sentiment, and PII Flag
Use brief rationales for designated edge cases
Note ambiguities and propose one guideline clarification

Your goal

Produce clear, consistent labels for a small batch of messages
Practice privacy-aware judgment by identifying and flagging PII
Build confidence with guidelines so similar items get similar labels
Prepare for basic reviewer decisions you’ll practice later in the simulation

Reviews

Over 6850

5 Star Reviews

"The organized structure, and overall flow of this simulation. Moving from initial label annotation into label review was highly beneficial for me in areas I could improve on and provided a much clearer picture of expectations."-- Student from Pasadena City College

"I liked how the simulation provided hands-on practice with real-world scenarios, especially the focus on intent, sentiment, and PII labeling. The step-by-step progression and review tasks helped reinforce understanding and build confidence."-- Student from Rajiv Gandhi Proudyogiki Vishwavidyalaya

"I'd say the instructions and guidelines provided before starting the tasks were clear and easy to understand. Great work, Forage team"-- Student from Egerton University

"I most important thing I liked about this simulation is various types of examples to one case which was really helpful to understand."-- Student from Shivaji University

"I liked that the simulation used realistic examples and helped improve decision-making skills for intent, sentiment, and PII labeling."-- Student from K L University

key 'simulation.landing.catalogueSection.heading (en)' returned an object instead of string.