Welcome to AI Data Annotation

01 Course Orientation

Welcome to AI Data Annotation Video
Introduction to Artificial Intelligence Locked
AI and data basics Locked

02 Module 1 — Workplace Communication

Professional communication Locked
Reporting standards Locked
Documentation practices Locked
Communication in AI projects Locked
Activity 1: Team communication exercise Locked
Module 1 — Workplace Communication — Knowledge Check Locked

03 Module 2 — Teamwork & Collaboration

Working in annotation teams Locked
Project coordination Locked
Escalation procedures Locked
Workflow collaboration Locked
Activity 2: Team annotation simulation Locked
Module 2 — Teamwork & Collaboration — Knowledge Check Locked

04 Module 3 — Problem Solving & Analytical Thinking

Identifying annotation errors Locked
Resolving inconsistencies Locked
Data quality troubleshooting Locked
Activity 3: Data correction exercise Locked
Module 3 — Problem Solving & Analytical Thinking — Knowledge Check Locked

05 Module 4 — Safety, Ethics & Professionalism

Workplace ethics Locked
Responsible AI Locked
Data confidentiality Locked
Ethical annotation standards Locked
Activity 4: AI ethics and compliance Locked
Module 4 — Safety, Ethics & Professionalism — Knowledge Check Locked

06 Module 5 — Apply Quality Standards

Data quality standards Locked
Annotation consistency Locked
Quality assurance procedures Locked
Review workflows Locked
Activity 5: Quality review exercise Locked
Module 5 — Apply Quality Standards — Knowledge Check Locked

07 Module 6 — Computer Operations

File management Locked
Spreadsheet basics Locked
Cloud storage usage Locked
Dataset organization Locked
Activity 6: Managing annotation datasets Locked
Module 6 — Computer Operations — Knowledge Check Locked

08 Module 7 — Data Privacy & Ethics

Privacy regulations Locked
Data protection Locked
Ethical AI practices Locked
Secure handling of datasets Locked
Activity 7: Privacy violation scenarios Locked
Module 7 — Data Privacy & Ethics — Knowledge Check Locked

09 Module 8 — Data Sources

Types of Data Sources Locked
Data Formats Locked
Data Quality Metrics Locked
Ethical Considerations Locked
Activity 8: Dataset evaluation exercise Locked
Module 8 — Data Sources — Knowledge Check Locked

10 Module 9 — Data Collection Planning

Collection Methods Locked
Collection Tools Locked
Secure Data Collection Locked
Workflow Planning Locked
Activity 9: Data collection planning Locked
Module 9 — Data Collection Planning — Knowledge Check Locked

11 Module 10 — Data Preparation

Organizing Data Locked
Data Cleaning Locked
Metadata Documentation Locked
Data Validation Locked
Activity 10: Cleaning raw datasets Locked
Module 10 — Data Preparation — Knowledge Check Locked

12 Module 11 — Data Collection Methods

Surveys & Forms Locked
API Collection Locked
Web Scraping Fundamentals Locked
Validation Techniques Locked
Activity 11: Lab — Simple data collection exercise Locked
Module 11 — Data Collection Methods — Knowledge Check Locked

13 Module 12 — Data Aggregation

Combining Data Sources Locked
Data Transformation Locked
Duplicate Checking Locked
Integrity Verification Locked
Activity 12: Merging datasets Locked
Module 12 — Data Aggregation — Knowledge Check Locked

14 Module 13 — Data Quality Management

Dataset Organization Locked
Backup & Recovery Locked
Access Controls Locked
Monitoring Quality Locked
Activity 13: Data quality standards Locked
Module 13 — Data Quality Management — Knowledge Check Locked

15 Module 14 — Annotation Fundamentals

Annotation Concepts Locked
Annotation Standards Locked
Data Types Locked
Project Requirements Locked
Activity 14: Annotation guideline review Locked
Module 14 — Annotation Fundamentals — Knowledge Check Locked

16 Module 15 — Performing Data Annotation

Annotation Tools Locked
Annotation Techniques Locked
Accuracy Checking Locked
Annotation Reviews Locked
Activity 15: Image annotation exercise Locked
Module 15 — Performing Data Annotation — Knowledge Check Locked

17 Module 16 — Data Labeling

Labeling Standards Locked
Dataset Categorization Locked
Label Verification Locked
Project Compliance Locked
Activity 16: Dataset labeling activity Locked
Module 16 — Data Labeling — Knowledge Check Locked

18 Module 17 — Documentation & Submission

Workflow Documentation Locked
Storage Requirements Locked
Submission Procedures Locked
Metadata Requirements Locked
Activity 17: Complete annotated dataset submission Locked
Module 17 — Documentation & Submission — Knowledge Check Locked

19 Final Assessments

Final Capstone: AI dataset annotation project Locked
Practical Examination Locked

Welcome to AI Data Annotation

Welcome to AI Data Annotation

Welcome to Data Collection and Annotation Level II! This program builds the practical, workplace-ready skills used in AI data collection and annotation. You will move step by step from foundational concepts to hands-on application, following industry and TESDA-aligned standards.

How this course works

Each module has short lessons, a stock-photo overview, an example video, a hands-on activity, and a short quiz.
Work through lessons in order — later modules build on earlier ones.
Pass each module quiz and the final exam to complete the course and earn your certificate.

Use the curriculum sidebar to track your progress and jump between lessons at any time. Let's begin.

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