AI Trainer Academy
Free modules on rating model answers, writing rubrics and passing platform screens. Your profile goes into the talent pool.
What the Academy gives you
Short modules
Rating model answers, writing rubrics, spotting label noise and passing platform screens, in the order platforms test them.
Get Referred
Build a profile and we'll reach out when we see a role you fit. No cold applications. Learn more →
Build Your Profile
Showcase your skills, experience, and expertise to attract opportunities from major companies.
Get Certified
Prove your skills with a verifiable certificate. Share it on LinkedIn and with recruiters in one click.
Everyone starts here. No prior knowledge needed.
How AI Training Jobs Work
Find out what AI annotation is, what the work looks like day-to-day, what separates people who get consistent work from people who don't, and how to figure out which income tier you can target.
Passing the Screening Process
Most candidates fail screening not because they lack the skills, but because they don't know what is being tested. This module breaks down every stage, the most common failure modes at each, and how to prepare for the real thing.
Your First Annotation Task
Walk through a complete pairwise comparison task step by step. By the end you've made a real annotation decision, written a rationale, and know what quality means in practice.
Essential skills every annotator needs regardless of specialisation.
Foundations of RLHF
Understand how reinforcement learning from human feedback (RLHF) works end to end, from pretraining to the final reinforcement step, and learn exactly what annotators do, why quality signals matter, and how your feedback shapes model behavior.
Ground Truth Research Method
Learn how to research claims rigorously, build verifiable rationales with primary sources, and meet the evidence standards required for high-paying expert reviewer roles.
Advanced Instruction Following
Master the skill of parsing complex, multi-part instructions, handling constraint conflicts, and telling a response that follows the instruction from one that only appears to.
Safety & Content Policy Triage
Learn when an AI must refuse, when it must help, and how to catch the error no annotator can afford to miss: the over-flag. Master the triage judgment that separates trusted reviewers from suspended accounts.
Structuring & Formatting Data for AI
Learn to spot the Markdown and JSON formatting errors that break AI training data: fake headings, broken tables, and invalid data structures. No coding background needed, since the job is checking output rather than writing it.
Final Practice: Full Task Simulation
Zero theory. Ten unguided, high-fidelity tasks covering every skill in the Core curriculum: hallucination hunting, constraint parsing, safety triage, ground truth verification, JSON auditing, tone evaluation, and multi-constraint judgment. This is your warm-up before real work.
Take this if you'll work on Python, SQL, or data evaluation tasks.
Python for AI Training
Learn what coding interview tasks and code review sessions test: correctness, complexity, edge cases, and style. Discover how to evaluate AI-generated Python as a professional annotator.
SQL & Data Handling
Build the SQL and data reasoning skills needed to evaluate AI-generated queries, spot logic errors in data analysis, and succeed in data science interview tasks.
Live Code Review & Debugging Interviews
Prepare for live, screen-share coding interviews where you debug real code out loud with an interviewer. Learn the narration habits and debugging loop that make the difference between a silent correct fix and a scored one.
Only take the track that matches your background. You don't need all of them.
Creative Writing & Style Guide Adherence
Learn what creative writing tasks in AI training require: style guide adherence, prompt engineering, brainstorming quality, red teaming for creative content, and what writing interviewers look for.
Medical Scribing & HIPAA for AI
Understand clinical case study format, core medical terminology, HIPAA's implications for AI training data, and how to evaluate AI medical responses against provided sources without a clinical background.
STEM & LaTeX (Math Solving)
Learn to write and evaluate mathematical reasoning with LaTeX, verify AI-generated STEM solutions step by step, and understand what olympiad-level and quantitative reasoning tasks require.
Foundations of Embodied AI & Robotics Annotation
Understand how robotics and embodied AI training data is labeled: 3D object perception, segmenting continuous motion into discrete steps, reading robot telemetry alongside video, and writing the instruction language that ties it together.
Robot Failure Taxonomy & Edge-Case Diagnosis
Classify why a robot attempt went wrong instead of describing what happened. Covers the perception, planning, and execution failure families, the control test that separates a drop from a failed grasp, recovery behavior, and why rubrics define numeric thresholds.
Egocentric Video Annotation & Human-to-Robot Imitation
Label first-person footage from head-mounted cameras and smart glasses: separating active from passive objects, locating the point of no return in an interaction, breaking procedures into atomic actions, and working with gaze as an intention signal.
Take these before a screening exam or a domain interview stage.
Screening Exam Concepts: Behavioral Economics & Decision-Making
Some screening exams test named concepts from behavioral economics and experimental design, not general knowledge. This module teaches you to recognize the concept being tested so a trick question stops looking like a trick.
Reading the Rubric Like a Grader
Domain and technical interview stages often score your response against a structured rubric, not a general impression. This module breaks down what a rubric criterion is made of, so you can read one the way the person grading you does.
Practice for free, then get certified
Practice Assessment
20 questions, same format as the official certification, no time pressure, full answer explanations. Free to retake as many times as you like.
Certified AI Training Fundamentals
Pass at 80% to earn a verifiable credential. Add it to your CV and LinkedIn to stand out to Outlier, Mercor, and DataAnnotation.
Role-Specific Interview Questions
289 roles, 2,890 questions with in-house written answers, covering technical, scenario, and behavioral rounds.
Modules take about 20 minutes each. Finish the first one today.
A free account opens every module, keeps your progress and builds the profile we use to put you forward for roles.
Sign Up Free