Udemy
Generative AI : LLM, Fine-tuning, RAG & Prompt engineering
Artificial Intelligence · IT & Software
Library / Artificial Intelligence
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SAP Generative AI Developer Practice Exam is a comprehensive learning and assessment resource designed to help learners, software developers, SAP consultants, technology professionals, and aspiring AI engineers prepare for topics related to generative artificial intelligence within the SAP ecosystem. The practice exam focuses on developing a strong understanding of generative AI concepts, large language models (LLMs), prompt engineering, retrieval-augmented generation (RAG), AI application development, responsible AI practices, and the integration of intelligent applications with SAP business processes and enterprise data. It provides a structured approach to reviewing theoretical knowledge, strengthening technical understanding, and applying concepts to realistic business and development scenarios.
Generative AI is becoming increasingly important in modern enterprise software because organizations need intelligent solutions that can understand natural language, summarize complex information, generate useful content, answer questions, assist with decision-making, and automate repetitive tasks. SAP provides an extensive enterprise technology ecosystem that supports business processes such as finance, procurement, supply chain management, human resources, sales, manufacturing, and customer experience. By combining generative AI capabilities with SAP applications and business data, developers can build solutions that help organizations improve productivity, simplify workflows, and provide more personalized user experiences. Therefore, understanding how generative AI can be applied to enterprise environments is an important skill for developers working with modern SAP technologies.
This practice exam is intended to help candidates understand the fundamental principles and practical applications of generative AI development in SAP-related environments.
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Udemy: 2026-10-22 · Coursera: 2026-10-22 · O'Reilly: 2026-10-22 · 365 Data Science: 2026-10-22
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