{"id":14876,"date":"2026-08-10T11:20:16","date_gmt":"2026-08-10T11:20:16","guid":{"rendered":"https:\/\/nokobox.com\/index.php\/item\/udemy-generative-ai-explained-from-math-basics-to-llms-2026-4\/"},"modified":"2026-08-10T11:20:16","modified_gmt":"2026-08-10T11:20:16","slug":"udemy-generative-ai-explained-from-math-basics-to-llms-2026-4","status":"publish","type":"digital_item","link":"https:\/\/nokobox.com\/index.php\/item\/udemy-generative-ai-explained-from-math-basics-to-llms-2026-4\/","title":{"rendered":"Udemy \u2013 Generative AI Explained From Math Basics to LLMs 2026-4"},"content":{"rendered":"
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Description<\/h2>\n

Generative AI Explained From Math Basics to LLMs is a generative AI course that bridges the gap between mathematical fundamentals and modern large-scale language models, published by Udemy Online Academy. This course is a comprehensive introduction to generative AI that bridges the gap between mathematical fundamentals and modern large-scale language models. Designed for developers, data scientists, students, and AI enthusiasts, this course explains the essential mathematics behind machine learning before progressing to deep learning, transformer architectures, and generative AI systems. You\u2019ll start with how machines see and prepare data, the types of data that AI works with, numerical challenges like overflow and underflow, and why normalization is essential before learning any model. From there, you will build the mathematical intuition behind AI: vectors, dot products, cosine similarity, and the equation that serves as the backbone of all machine learning.<\/p>\n

People will learn linear algebra, probability, calculus concepts, neural networks, attention mechanisms, embeddings, tokenization, training processes, rapid engineering, and the inner workings of large language models (LLMs). Finally, you will get to transformer architecture, the advancement that powers every major generative AI model today. You will learn about tokenization, situational coding, attention mechanisms (including query, key, and value matrices), multi-head attention, and how encoder-only, decoder-only, and encoder-decoder models serve different purposes in the industry.<\/p>\n

What you will learn in Generative AI Explained From Math Basics to LLMs:<\/h3>\n