Artificial Intelligence I ISO/IEC 22989:2022 Training – Part 4 | Clause 5.5 to 5.10 Explained скачать в хорошем качестве

Artificial Intelligence I ISO/IEC 22989:2022 Training – Part 4 | Clause 5.5 to 5.10 Explained

Edicent Quality Registrar (EQR) Services: Certification, Training and Advising Contact Details: +91-8802650960; info@edicentcertification.org 📘 ISO/IEC 22989:2022 Training – AI Concepts (Clause 5.5–5.10) In this detailed session of our ISO/IEC 22989:2022 series, we explore advanced AI concepts covering Cognition, Semantic Computing, Soft Computing, Genetic Algorithms, Symbolic vs Subsymbolic AI, and Data Foundations within the ML lifecycle. This part strengthens conceptual clarity for AI governance, system design, and standardization alignment. 🔹 Cognition & Cognitive Computing Artificial Intelligence draws heavily from cognitive science. This section explains: Knowledge acquisition and processing Reasoning based on exclusive and shared experiences Learning and perception mechanisms Core cognitive functions: Attention, memory, knowledge formation, judgment, evaluation, reasoning, computation, problem solving, decision making, and language comprehension & production We also discuss AI subdisciplines that replicate or simulate cognitive behavior in computational systems. 🔹 Semantic Computing Semantic computing focuses on: Matching and representing meaning in information Retrieving, managing, manipulating, and creating content Reducing uncertainty through structured representation Logical reasoning by combining prior knowledge with learned information This is foundational for knowledge graphs, intelligent search, and contextual AI systems. 🔹 Soft Computing Unlike rigid computational models, soft computing: Tolerates imprecision, uncertainty, and partial truth Uses techniques such as: Fuzzy systems Evolutionary algorithms Swarm intelligence Neural network systems Soft computing enhances adaptability and robustness in real-world AI applications. 🔹 Genetic Algorithms Inspired by biological evolution, genetic algorithms: Simulate natural selection and mutation Represent solutions as gene sets (often binary: 0s and 1s) Evaluate performance through fitness calculation Improve solutions via: Ranking Crossover of chromosomes Mutation Continue until defined termination criteria are met Select the fittest chromosomes as optimal or near-optimal solutions These are powerful for optimization problems in complex environments. 🔹 Symbolic vs Subsymbolic AI We explore the two foundational AI paradigms: ✔ Symbolic AI Explicit knowledge encoding Logical models and formal representations Clear syntax–semantics distinction Rule-based reasoning ✔ Subsymbolic AI Connectionist paradigm Implicit knowledge encoding Statistical and machine learning approaches Deep neural networks We also examine Hybrid AI, which integrates both paradigms for enhanced capability. 🔹 Data in AI & Machine Learning Lifecycle Data is central to AI system development and testing. This session covers: Structured and unstructured data forms The ML lifecycle stages: Data acquisition Exploratory data analysis (EDA) Data annotation Filtering & normalization De-identification Quality checking Data sampling Understanding data governance and lifecycle integrity is critical for trustworthy AI systems aligned with ISO/IEC standards. 🎯 Who Should Watch? AI professionals & researchers Data scientists & ML engineers AI governance & compliance leaders ISO standard practitioners Technology risk & assurance professionals This training strengthens your conceptual foundation under ISO/IEC 22989:2022 AI terminology and concepts framework, enabling better alignment with emerging AI governance and assurance standards. Stay tuned for the next part of the series. 🚀 With the help of this channel, we want to refine thinking about international standards knowledge and implementation, as we worked over more than 3000 companies since 2014, we are seeing a gap in understanding and relating the information of standard in implementation, in practices of system management the management team is feeling standards as obstacle but all business leaders globally have a strong management system and their sustainability key, any scale business should collapse and taken over by any strong management system business. Compliance of any international standard has three pillars management team, audit, and training only, it adds more valuable than marketing in short and long term run, compliance importance and usefulness is all belong to a business internally itself not on external dependence. You may connect for our service at www.edicentcertification.org, please like, subscribe and share. Bank account details for your support EQR Account Detail: Bank Name: HDFC Bank Current Account Name: Edicent Quality Registrar Current Account Number: 50200086783433 IFSC Code: HDFC0005269 SWIFT Code: HDFCINBBDEL UPI ID: 8882814173@hdfcbank Paypal ID: https://paypal.me/EQRQuality Thank you.