AI Quality Certification Program

AI Quality Certification Program (AIQCP)

A comprehensive set of practical trainings to master AI & Data quality

A comprehensive set of practical trainings to master AI & Data quality

ABOUT THE AI QUALITY CERTIFICATION PROGRAM (AIQCP)

The AI Quality Certification Program (AIQCP) is a certified training program that provides individuals and organisations with the necessary knowledge and skills to effectively manage the quality of AI systems and products across all organisational functions and industries.

This program has two levels and focuses on the assessment and assurance of AI quality, comprising safety, security, legal, ethics, performance, and sustainability aspects. Level 1 provides foundational knowledge on AI quality, while Level 2 concentrates on the practical implementation of AI quality management systems.

Participants in this program, led by AI experts actively involved in standardisation, regulation, and practical implementation of AI quality management systems, will gain valuable insights into internationally accepted methodologies, standards, regulations, and best practices for assuring the quality of AI.

The course provides course materials, templates, and guidance for implementing AI quality management systems. Upon completion and successful examination, participants will be awarded a certificate, proving their competence and ability to assume AI and data quality management responsibilities within their organisations.

This course is a vital foundation for scaling AI, complying with regulations, and demonstrating responsible AI use to mitigate financial, legal, and reputational risks.

Language: English

WHAT WILL YOU LEARN FROM THE COURSE?

  • Importance and impact of AI in various industries and societies.
  • Challenges and failures in AI and strategies to address them.
  • AI system architecture and design principles.
  • Identification of AI stakeholders and their roles.
  • AI quality model: safety, security, legal compliance, ethics, and performance.
  • Risk assessment for AI implementation.
  • AI governance process framework and controls.
  • AI data quality and data life cycle management.
  • Application of AI quality frameworks in daily operations.
  • AI standards and regulatory activities.

COURSE CONTENT

 

  • AIQCP Foundation: Level 1 – Engineer

    1. Motivation and requirements
    • Introduction to AI and the need for AI quality
    • Current and upcoming standards and regulation of AI
    • Roles, responsibilities and liabilities

    2. AI quality
    • Terms and definitions
    • Key pillars of AI quality
    • The AI quality life cycle
    • AI quality management

    3. AI quality framework
    • Methodology and key elements to establish an AI quality management system
    • AI governance requirements
    • AI quality management in a case study
    • IEEE AI ethics

    4. Applying AI framework
    • Plan an AI quality management system
    • Control of AI quality parameters
    • Testing and assessing AI

    5. Examination
    • Multiple Choice Test

  • Schedule: AIQCP Level 1

    Region

    Dates

    Training Time (Timezone)

    Europe / Middle East

    Training:

    16 – 18 Oct

    CEST: 0900hrs – 1300hrs
    (UTC +2)

    Examination:

    18 Oct

    CEST: 1400hrs – 1500hrs
    (UTC +2)

    ASEAN

    Training:

    13 – 15 Nov

    SGT: 1300hrs – 1700hrs
    (UTC +8)

    Examination:

    15 Nov

    SGT: 1700hrs – 1800hrs
    (UTC +8)

  • AIQCP Professional: Level 2 – Practitioner

    This training builds on the AIQCP Engineer Level 1 and enables to apply the AI quality framework to concrete AI products and systems. Participants will also gain an overview of the latest developments in regulations and standardisation. A minimum of 1 year of industry experience in AI quality management are beneficial.
    Participants aims at taking over AI quality responsibilities

    Course content:
    1. Recap of AI quality
    • AI quality framework concepts
    • Relevant standards and regulations
    • Application methodology, tools and templates
    • Qualitative and quantitative metrics

    • IEEE AI ethics
    2. Application of AI quality framework
    • Introduction to use cases
    • Step-by-step implementation process
    • Design of an individual AI QMS use case

    3. Analysis
    • Presentation and discussion of use case
    • Refinement of use case based on lessons learned
    • Compiling of an AI quality report for the use case

    4. Examination
    • Multiple Choice Test
    • Design AI QMS to given use case

WHAT IS THE COURSE METHODOLOGY?

Participants will learn through lectures, case studies, group exercises and discussions.

WHO SHOULD TAKE THE COURSE?

This programme is aimed at professionals who want to understand, control and manage quality of AI and are involved in projects at any stage of the AI life cycle, from conception to decommissioning:

  • AI Developers and Engineers
  • AI Practitioners and Data Architects
  • Data Engineers and Scientists
  • Quality and Technology Managers
  • Software Developers and Engineers
  • System Administrators

WHO IS THE COURSE ADVISOR?

The course content and structure are designed by top TÜV SÜD experts for AI Quality.

With immense experience and knowledge in the relevant standards, our team of product specialists and technical experts at TÜV SÜD, developed the course content based on current business landscape and market requirements.

FREQUENTLY ASKED QUESTIONS

Next Steps

Site Selector