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PCiDS™ Qualifying and Certification Rounds
To earn the prestigious PCiDS™ Certificate, the process consists of two stages. The first stage must be completed within three months. All exam-takers must strictly adhere to the following instructions:
Stage 1 - Qualifying Round
You will be given a scenario and are required to complete the following tasks:
- Write a detailed report of at least 3,500 words assessing the scenario, addressed to the management.
- Present the report in a video recording, summarizing your assessment in no more than 20 minutes.
Detailed Report
The report must include the following components:
- AI Use Disclosure & Provenance
- Cover Page
- Table of Content
- Executive Summary
- Scenario & Objectives (Domain Context)
- Data Inventory, Governance & Quality
- Data Integration & ETL (Reproducible Workflow)
- Exploratory Analysis & Domain Modeling
- Analytical/ML Methods & Performance
- Experimentation & Measurement Plan
- Ethics, Legal & Compliance
- Recommendations, Roadmap & Economics
- Limitations, Risks & Next Steps
- Personal Reflection
- Appendices (as applicable)
Important:
Any content with a high similarity to AI-generated material will result in a deduction of marks. It is the trainee’s responsibility to ensure the report reflects original thought and demonstrates minimal similarity to AI-generated outputs.
Video Presentation
After completing the detailed report, the trainee must record a video presentation with the following requirements:
- The trainee must be dressed in professional attire and appear in a professional setting.
- Eye contact with the camera must be maintained throughout the presentation, except for brief glances (e.g., when referencing notes).
- Reading directly from a script will result in mark deductions.
- The video should present a concise and structured summary of the report within the allocated time limit.
Important:
The trainee must present the biographical page of their passport or the front of their photo ID with the photo, showing their photo alongside their face, in the video before the presentation begins. The name printed on the passport or ID must be the same as the registered name with Data Chord. The certificate will be issued to the name found in the passport or ID.
Optional:
Trainees are encouraged to use video editing tools to enhance the presentation quality.
Alternatively, the trainee may present the report in a videoconference-style format, delivering the presentation to a live audience via platforms such as Microsoft Teams or Zoom.
Criteria
Trainees must achieve a minimum score of 70% to advance to the Certification Round. In the event of failure, trainees may retake Stage 1 by paying the examination fee again.
Post-Submission after Stage 1
Stage 2 - Certification Round
Upon completing the stage 1 qualifying round with at least a pass of 70% mark, the candidate will receive an invitation to be interviewed by one of the expert panel assessors. The interview typically happens within 1 month after obtaining a pass for stage 1.
During the interview, the candidate must:
- Explain the rationale behind the techniques, tools, and models used in Stage 1
- Justify decisions made in data integration, modeling, and machine learning application
- Clarify the approach taken in addressing ethical and legal considerations
- Respond to additional what-if scenarios or variations of the original case
- Propose alternative solutions or improvements to the existing recommendations
- Demonstrate integration of concepts
- Provide real-world analogies or examples to support explanations
- Maintain clarity, structure, and coherence when responding
Important:
- The candidate is expected to perform some prior research before attending the interview.
- The candidate must present the biographical page of their passport or the front of their photo ID with the photo, showing their photo alongside their face, in the video call prior to the start of the interview.
Interview Format:
- Conducted via video conferencing tools (e.g., Zoom, Microsoft Teams)
- Duration: 30–45 minutes
- Panelist(s): 1–2 expert assessors
- The session will be recorded for verification and quality assurance
The candidate must achieve a PASS decided by the assessor(s). Upon passing stage 2 which is the certification round, the candidate will receive the e-certificate within 7 working days. Candidates may request for a hardcopy at an additional fee.
Expert Assessment Panel
Dr. Daniel Koh
Dr. Kathrin Kind-Trueller
Dr. Kathrin Kind-Trueller
With over 20 years of experience in data science across multiple markets and more than 7 years as a university lecturer, Dr. Daniel Koh brings deep expertise at the intersection of data, education, and innovation. He has worked extensively with both government agencies and private enterprises to develop data-driven strategies for decision
With over 20 years of experience in data science across multiple markets and more than 7 years as a university lecturer, Dr. Daniel Koh brings deep expertise at the intersection of data, education, and innovation. He has worked extensively with both government agencies and private enterprises to develop data-driven strategies for decision-making and digital transformation. Dr. Koh is the founder of Koh & Associates in Osaka and the Managing Director of the Singapore-based affiliated company, Data Chord Pte Ltd. His programs blend rigorous analytical training with practical, real-world application, preparing trainees not just to understand data—but to lead with it. He is also actively involved in building bridges between regional talent and international opportunities, particularly in high-impact areas such as data science and AI. In recognition of his contributions to Singapore’s national efforts during the COVID-19 pandemic, Dr. Koh was awarded the COVID-19 Resilience Medal, honoring his role in using data science to support public initiatives during a time of crisis. Trainees who successfully complete his programs emerge with the technical competence, critical thinking, and global mindset necessary to thrive in fast-changing, data-intensive environments.
Dr. Kathrin Kind-Trueller
Dr. Kathrin Kind-Trueller
Dr. Kathrin Kind-Trueller
One of only 20 globally curated members of the World Economic Forum’s Global Future Council on Data Frontiers, Dr. Kathrin Kind-Trueller is a distinguished, multi-award-winning expert in the application of artificial intelligence to business. She began her career in 1999 in quality engineering for international mobile communication networ
One of only 20 globally curated members of the World Economic Forum’s Global Future Council on Data Frontiers, Dr. Kathrin Kind-Trueller is a distinguished, multi-award-winning expert in the application of artificial intelligence to business. She began her career in 1999 in quality engineering for international mobile communication networks at Siemens. Over the years, she has contributed to the development of complete vehicle functions—including ADAS, engine management, steering, braking, cockpit infotainment, and autonomous driving—at top-tier automotive suppliers such as Bosch, ZF-TRW, and Magneti Marelli, as well as OEMs like BMW (Munich), Mercedes-Benz Cars (Sindelfingen), and Audi (Ingolstadt). She later served as a senior research scientist in AI for the Volkswagen Group in Wolfsburg.
Dr. Kind-Trueller currently holds the position of Chief Data Scientist and AI Director for Cognizant in Global Growth Markets. She is also a Technical Editor for CRC Press and Springer Nature, a volunteer mentor with the KALAI initiative under ICT, and a guest lecturer at the University of Agder (Norway) and the University of New Delhi. A prolific academic, she is the author and co-author of several technical books on autonomous systems and data.
Her academic background includes a Doctorate in AI applied to business from SSBM Geneva in collaboration with the University of Zagreb, an MBA in AI from the University of Cumbria, an MSc in Computer Science and Software Engineering from the University of Hertfordshire, and a Master of Arts in Leading Innovation and Change from York St. John University. She also holds Postgraduate Diplomas in Digitalisation Leadership from Columbia University and Systems Engineering from MIT (USA). With her expertise in data science and AI, we are confident that she brings great value to our professional certificate in data science program.
Teh Siew Yee
Dr. Kathrin Kind-Trueller
Teh Siew Yee
Teh Siew Yee, MITB, M.Sc., B.Eng., is a seasoned consultant, trainer, and lecturer in Artificial Intelligence, Data Science, and Digital Transformation with over 25 years of global and Asia Pacific experience across education, technology, telco, banking, aerospace, eCommerce, B2B, retail, social media, and advertising. She has held leade
Teh Siew Yee, MITB, M.Sc., B.Eng., is a seasoned consultant, trainer, and lecturer in Artificial Intelligence, Data Science, and Digital Transformation with over 25 years of global and Asia Pacific experience across education, technology, telco, banking, aerospace, eCommerce, B2B, retail, social media, and advertising. She has held leadership roles such as Head of Asia Pacific (Insights) at a global MNC, Analytics Director in a media agency, and Head of Data Engineering & Analytics at SIA Engineering Company, where she led large multi-country teams to drive digitalisation, data democratization, and business impact. A corporate trainer in Data Storytelling, Visualization, and WSQ-accredited courses—including LLMs, Agentic AI, Neo4j, Blockchain, and Microsoft Copilot—she also lectures in analytics, data science, and robotics at the undergraduate and postgraduate level. With academic credentials spanning a Master of IT in Business (AI, Distinction) from SMU, an MSc in Marketing, and a B.Eng. in Electrical & Electronics Engineering, she combines academic rigor with industry practice, has published on fuzzy control in robotics, and is multilingual in English, Chinese, and Malay.