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₦ 20,000.00
One Outcome: You Can Do the Work Powering AI Systems Today.
Every major AI system in use today was shaped by humans who labeled data, evaluated responses, and flagged errors before that system ever reached the public. That work - data annotation, classification, AI evaluation - is real, paid, remote work, and demand for people who can do it properly is growing faster than almost any other category of remote job. This is the Academy's most in-depth course: six focused classes, because this is genuinely the newest and most specialized skill of the four, and it deserves the room to actually build competence, not just familiarity.
Who This Is For
No prior AI, tech, or data background required. This suits anyone with strong attention to detail and the patience to follow instructions precisely - recent graduates, career-changers, and anyone curious about AI who wants a real skill in it rather than just an opinion about it. If you can read carefully, follow guidelines exactly, and stay consistent across repetitive tasks, you're the right fit.
What You'll Be Able to Do When You're Done
Explain, in plain terms, how AI systems actually learn from data - and where human input fits into that process
Follow detailed annotation guidelines accurately and consistently
Classify and label text data - sentiment, intent, categorization, entity identification
Understand the basics of image, audio, and video annotation
Evaluate AI-generated responses against a quality standard - accuracy, relevance, safety
Speak knowledgeably about human-in-the-loop AI work in an interview, because you've actually done sample annotation and evaluation tasks, not just read about them
The 6 Classes
Class 1 - Understanding AI Work
What AI actually is, the basics of how machine learning systems learn, what training data means in practice, and the different categories of human-in-the-loop AI work - annotation versus evaluation.
Class 2 - Data Annotation Fundamentals
Labeling, classification, categorization, entity identification, and why consistency matters more than speed. Practical: annotate sample datasets under real guidelines.
Class 3 - Text & Language Data
Text classification, sentiment and intent detection, entity extraction, and evaluating how well an AI response follows an instruction. Practical: evaluate and label sample text data yourself.
Class 4 - Image, Audio & Video Data
An introduction to image classification, object identification, audio transcription basics, and video annotation concepts. Practical: complete sample annotation tasks across formats.
Class 5 - AI Evaluation & Quality Assurance
How to evaluate an AI-generated response for accuracy, relevance, helpfulness, and safety, how to identify errors, and why consistency between annotators matters. Practical: evaluate AI-generated outputs against a real guideline sheet.
Class 6 - AI Annotation Capstone
You're given a structured annotation and evaluation project and have to understand the instructions, apply the guidelines, complete the task, check your own work, and explain your decisions - the exact standard a real annotation project would hold you to.
What You Leave With
An "AI Data & Evaluation Portfolio" - completed text annotation samples, classification work, and AI response evaluations you produced yourself, checked against real quality standards - plus everything every Academy participant gets: your ebook, the Remote Work Blueprint, a CV review, and a certificate.
Cohort 1 Dates
30th November - 11th December 2026.
Live online.
Enrollment closes on 27th November 2026
Want More Than One Skill?
AI Training & Data Annotation is the Academy's most specialized path - many participants pair it with Virtual Assistant for a broader remote-work base. See the full bundle pricing - including the Full Academy Pass - on the main Academy page.
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