ISO 42001/22989: Fundamentals of Artificial Intelligence -AI

In this course, you will master the common AI language according to ISO/IEC 22989 and its practical connection to ISO/IEC 42001 governance. Based on our project sessions (AI ecosystem, lifecycle, symbolic/subsymbolic AI, data quality checking, IoT, and ML algorithms), upon completion, you will be able to:Accurately interpret the official definitions of AI systems, models, data, datasets, training, validation, and deployment.Differentiate between symbolic and subsymbolic AI and recognize hybrid approaches with clear examples.Locate the most common algorithms (SVMs, CNN/RNN/LSTM neural networks, decision trees, Bayesian networks) within the 22989 framework.Explain the lifecycle of an AI system, its artifacts, and the evidence required for auditing (traceability, logging, change control).Apply data quality checking: requirements, typical risks (bias, contamination), and minimum controls.Map terms and artifacts to ISO 42001 Annex A controls (technical documentation, data, monitoring, explainability, human intervention, incidents).Distinguish roles and responsibilities in an FSMS (process owners, data custodians, developers, auditors).Identify common risks (e.g., prompt injection and uncontrolled consumption) and their relationship to FSMS policies and metrics.Build a glossary and "data sheet" templates for models, data, and algorithmic decisions, ready for auditing.Learn from the most popular AI tools to understand concepts such as ChatGPT, Eleven Labs, Heygen, Sora, Explotion, among others.This course is designed to enrich your skills and knowledge, offering you practical and relevant tools for your professional development. Whether you are looking to improve your sustainability skills, or want to delve into advanced water management, this course is your gateway to a field of vital global importance. This course is cat