How We Train
Every annotation and evaluation task on SCILabel is performed by a healthcare professional who has completed SCI's structured, multi-course training programme. We do not use general-purpose crowd workers. Every tasker is a certified clinical professional.
Our Training Philosophy
Entry Requirements
The Four Training Courses
Programme Structure
SCI's training programme consists of four courses. Course 1 is the mandatory entry point — no tasker accesses paid work without completing it. Courses 2, 3, and 4 are specialist tracks that unlock premium-rate tasks and advanced roles. Courses can be completed sequentially or in parallel once Course 1 is underway.
Healthcare AI Trainer & Data Annotation Program
The Flagship — Mandatory for all SCILabel Taskers
- Module 1 — Foundations of AI in Healthcare
- Module 2 — Data Annotation Fundamentals
- Module 3 — Medical Image Annotation
- Module 4 — Clinical NLP Annotation
- Module 5 — RLHF & AI Response Evaluation
- Module 6 — Quality Assurance & Operations
- Module 7 — Data Privacy, Ethics & Regulatory
100 tasks using real-format healthcare data: DICOM, clinical text, NLP, RLHF, and QA workflows.
1 hour — Microsoft Teams — Timed annotation, Q&A, ethics scenario. Minimum pass: 75%.
Health Data Handling & Regulatory Compliance
Prerequisite for QA reviewer track and regulated-data projects
- Module 1 — HIPAA (US) — Privacy, Security, Breach
- Module 2 — GDPR (EU/EEA) — Lawful processing, DPO
- Module 3 — EU AI Act 2024 — Risk tiers & compliance
- Module 4 — FDA SaMD & WHO AI Ethics Framework
- Module 5 — Kenya DPA & African Data Governance
- Module 6 — Practical Application & Case Studies
Final proctored assessment. Minimum 80% pass score. Certificate within 5 business days.
Clinical AI Evaluation & RLHF Specialist
Unlocks premium RLHF rates and QA reviewer candidacy
- Module 1 — RLHF Foundations — Reward models
- Module 2 — Multi-Criterion Clinical Scoring
- Module 3 — Evaluation Interface & Workflow
- Module 4 — Red-Teaming & Safety Testing
- Module 5 — Bias & Fairness Assessment
- Module 6 — Clinical Benchmarking Standards
Two live workshop evaluations plus a final portfolio across at least two clinical domains.
Medical Image Annotation Specialist
DICOM-certified status and premium imaging task rates
- Module 1 — DICOM Fundamentals
- Module 2 — Radiology Annotation (CT, MRI, X-ray)
- Module 3 — Pathology Whole-Slide Annotation
- Module 4 — Ophthalmology — Retinal & OCT
- Module 5 — Dental Radiograph Annotation
- Module 6 — Advanced Techniques & QA
Three live practicum sessions with real DICOM datasets plus a final annotated portfolio.
Ready to build your career at the intersection of clinical expertise and artificial intelligence?
Join Our WorkforceLearning Infrastructure
SCI provides a complete, integrated learning ecosystem designed to prepare taskers for success in healthcare AI annotation and evaluation.
SCI Learning Canvas
All course content is delivered through the SCI Learning Canvas — SCI's branded online learning management system built on the Canva platform. Taskers access lesson content, practical assignments, progress tracking, and certification records through a single, mobile-accessible interface. Available 24/7 for self-paced study.
Microsoft Teams
Live competency evaluations, RLHF workshop sessions, and imaging practicum reviews are conducted via Microsoft Teams. All taskers receive a SCI Microsoft 365 education account providing access to Teams, OneDrive, and collaborative tools.
SCILabel Training Environment
Practical assignments are completed on a dedicated training environment of the SCILabel annotation platform — identical to the production workspace but populated with training-purpose de-identified data. This ensures taskers are fully familiar with the exact tools, interface, and submission workflow used on paid projects.
Continuous Development & Quality Standards
SCI maintains rigorous quality standards through continuous assessment, feedback, and professional development pathways.
Gold-Standard Benchmark Tasks
Once taskers are working on live paid projects, gold-standard benchmark tasks — pre-annotated by SCI's QA leads — are embedded passively in every task queue. Taskers do not know which tasks are benchmarks. Performance on these tasks provides a continuous, unbiased measure of annotation accuracy that feeds into each tasker's quality score.
QA Feedback & Learning Loop
Every task that fails QA review is returned to the tasker with specific, line-by-line feedback from the QA reviewer. Taskers are required to address feedback and resubmit. Patterns of recurring errors trigger a one-to-one coaching session with a QA lead. This creates a continuous improvement loop that raises quality over time rather than simply penalising errors.
Quality Score & Track Advancement
Every tasker has a visible quality score based on QA pass rates, gold-standard benchmark performance, and client satisfaction. Quality scores determine task priority: high-scoring taskers receive first access to high-value, premium-rate projects. QA leads may expand a tasker's approved tracks based on demonstrated quality performance, enabling career progression without re-enrolment.
CPD & Professional Development
SCI is pursuing CPD accreditation for its training programme with the Kenya Medical Association, Kenya Nurses Association, and Kenya Medical Laboratory Technicians and Technologists Board. Certified taskers will be able to count SCI training hours towards their annual CPD requirements. SCI also publishes regular knowledge-update materials as healthcare AI regulations and annotation best practices evolve.
From Training to Earnings — The Complete Pathway
Your journey from enrollment to earning — follow the steps below to become a certified SCILabel tasker and start earning.
| Step | Action | Timeline | Outcome |
|---|---|---|---|
| 1 | Enrol in the Course Bundle and pay via PayHero | Day 1 | Instant access to all four courses via SCI Learning Canvas |
| 2 | Complete Course 1: 109 lessons, 100 practical assignments | Weeks 1–6 | Eligible for live competency evaluation |
| 3 | Pass live competency evaluation (Microsoft Teams, 1 hour) | Weeks 7–8 | SCI Healthcare AI Certificate issued |
| 4 | Receive SCILabel Tasker ID; annotation workspace activated | Within 5 business days | Ready to accept paid tasks |
| 5 | Select availability; receive first tasks matched to specialist tracks | From activation | Earning bi-weekly via M-Pesa, bank transfer, or card |
| 6 | Complete Courses 2, 3, and 4 alongside paid work | Months 2–6 | Unlock regulated-data projects, RLHF premium rates, DICOM status |
| 7 | Maintain quality score; advance to QA reviewer candidacy (top performers) | From Month 3+ | QA reviewer role (higher base rate, supervisory responsibilities) |