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Understanding AI Auditing through Core Concepts

Feeling overwhelmed by where to start with AI auditing? AI has moved beyond a mere technology trend and is rapidly expanding into corporate decision-making, workflow automation, customer service, recruitment, security, and risk management. However, compared to the speed of AI adoption, not many people systematically understand questions like: "Is the AI being properly controlled?", "Can we trust the AI's judgment?", or "What risks could arise from the data, models, and operational processes?" In particular, those working in IT auditing, security, internal control, and project management often face these concerns: - How does AI auditing differ from traditional IT auditing? - Is it enough to just look at the code for an AI model, or must we examine the data and training process as well? - How do AI governance, risk, bias, explainability, MLOps, and incident response connect to one another? - Where should I start to understand the concepts covered in AI auditing certification courses like AAIA from a practical perspective? This course was created specifically to resolve this sense of uncertainty. For about 20 years, I have gained experience in IT service planning, development, PM, collaboration platform operation, groupware construction, chatbot service planning, and security and audit-related tasks. I have firsthand experience in how systems are planned, developed, and operated in actual organizations, and how failures, changes, security, and user requirements are interconnected. Furthermore, I have synthesized the perspectives of IT auditing and AI auditing through CISA and AAIA study programs. In this course, rather than diving deep into complex AI technology through math or development, I focus on the core concepts that auditors and IT practitioners must understand. We will examine AI systems by breaking them down into the flow of data, models, operations, security, governance, risk, and audit procedures, and summarize what controls and checkpoints are required at each stage. Through this course, students will understand that AI auditing is not simply "evaluating AI," but rather the task of inspecting governance, risk, and control systems to ensure that AI is used safely and responsibly within an organization. This course is suitable for: - Those new to AI auditing. - Those in IT auditing or security who want to expand into the AI domain. - Those who want to organize AI governance and risk from a practical perspective. - Those who want to grasp the overall concepts before starting AI audit-related studies such as AAIA. Upon completing the course, you will be able to answer the following questions yourself: - What components make up an AI system? - What should an AI auditor check during the data, model, and operation stages? - Why are AI governance and Responsible AI important? - How are AI risk, bias, explainability, privacy, and security connected? - What perspectives and evidence should be included in an AI audit report? In the rapidly changing era of AI, the ability to manage and inspect technology to make it trustworthy is just as important as the ability to use it well. This course is an introductory program for those who want to understand the big picture of AI auditing step-by-step from the beginning. Let's build the first standard for looking at IT and AI from an auditing perspective together.

1 learners are taking this course

Level Beginner

Course period 1 months

AI
AI
security training
security training
Data Engineering
Data Engineering
Project Management (PM)
Project Management (PM)
AI
AI
security training
security training
Data Engineering
Data Engineering
Project Management (PM)
Project Management (PM)

What you will gain after the course

  • AI systems can be understood by breaking them down from an auditing perspective.

  • I can explain the core concepts of AI governance and responsible AI.

  • You can create basic questions to identify AI risks.

  • You can organize the control points to be checked during the AI operation process.

  • You can understand the basic flow of AI auditing.

This is an introductory course for those new to AI auditing. It provides an easy-to-understand summary from an auditing perspective, covering everything from the basic structure of AI systems to data quality, model operations, AI governance, risk management, information security, privacy, bias, explainability, incident response, and the flow of writing audit reports.
This course does not simply explain AI terminology; it focuses on what risks can arise when an organization actually adopts and operates AI, and what auditors and IT practitioners need to verify.
It is designed to help those interested in IT auditing, security, internal control, and AI governance understand AI systems from the perspective of reliability and control.

Recommended for
these people

Who is this course right for?

  • Those who are new to AI auditing and want to grasp the overall concept.

  • Those who want to expand from IT audit, security, and internal control into the field of AI

  • PMs, planners, and IT professionals who plan and operate AI services

  • Those who are preparing to study audit and security-related certifications such as AAIA and CISA

  • Those who want to develop the sense of digital risk management necessary in the AI era

Need to know before starting?

  • There are no required prerequisites.

Hello
This is floria

Career Verified

Hello.
I am Floria, and I simplify knowledge from the perspectives of AI, IT, and auditing.

I have about 20 years of experience in IT service planning, development, project management, and the establishment and operation of collaboration platforms. By working on groupware, collaboration tools, chatbots, cloud-based services, and security and audit-related tasks, I have gained hands-on experience in how IT systems are planned, developed, and operated within actual organizations.

Currently, I am focusing on AI auditing, IT auditing, information security, digital risk, and AI governance, organizing both theoretical knowledge and practical perspectives in these fields. Based on my experience studying for CISA and AAIA, I focus on "how to manage and inspect technology to make it trustworthy," moving beyond the perspective of simply using it.

Rather than explaining complex technologies in a difficult way, the lectures I create aim to bridge core concepts with practical perspectives so that IT practitioners, audit beginners, security professionals, and planners can all understand them.

AI and IT are changing rapidly, but the importance of governance and control for using those technologies safely and responsibly is growing even more.
On this channel, I will break down topics related to AI auditing, IT auditing, information security, data governance, and digital risk step-by-step in an easy-to-understand way.

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