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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 cybersecurity scenario and are required to complete the following tasks: 

 

  1. Write a detailed report of at least 3,500 words assessing the scenario, addressed to the management.
  2. 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
    A signed statement declaring any use of AI tools and the practice of paraphrasing outputs, if applicable.
  • Cover Page
    Includes the student’s name, instructor’s name, and student ID (if applicable).
  • Table of Contents
    A clear outline of the sections included in the report.
  • Executive Summary
    A concise overview of your findings and key points.
  • Technical Description of the Incident
    Detailed analysis of the cybersecurity scenario, including logs, vectors, and patterns.
  • Data Integration & ETL Process
    A description of how various data sources were cleaned, transformed, and merged. Technical walkthrough must be provided.
  • Threat Modeling and Graph Analysis
    Graph-based representation and analysis of potential attack paths or anomalies. Technical walkthrough must be provided.
  • Machine Learning Model Use & Performance
    Explanation of ML techniques used, model evaluation, and performance metrics. Technical walkthrough must be provided.
  • Visualizations
    Graphs, charts, or dashboards that support the understanding of the report.
  • Drafted Ethical and Legal Documents
    Relevant documents (e.g., Data Protection Impact Assessment, ethical considerations) based on the scenario.
  • Recommendations & Prevention Plan
    Actionable strategies for mitigation and future prevention.
  • Personal Reflection
    Insights gained, challenges faced, and lessons learned.


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, threat 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 from AI, ETL, graph theory, ML, visualization, and ethical analytics
  • 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.

Accreditation

The PCiDS™ certificate issued by Data Chord is accredited by The Association of Data Scientists, the international body for data science and AI. 

Exam Details

28 June 2025 - alongside with the online PCiDS™ training program

16 July 2025 - alongside with the NextGen Tech Fellowship Program

21 August 2025 - alongside with the PCiDS™ face-to-face training program in Central Asia


US$300


Note: This exam fee is included in the PCiDS Training Program fee, both online and face-to-face.


Virtual submission via LMS


3 months to complete stage 1


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