This paper presents a technical curriculum on language-oriented artificial intelligence (AI) in the language and translation (L&T) industry. The curriculum aims to foster domain-specific technical AI literacy among stakeholders in the fields of translation and specialised communication by exposing them to the conceptual and technical/algorithmic foundations of modern language-oriented AI in an accessible way. The core curriculum focuses on 1) vector embeddings, 2) the technical foundations of neural networks, 3) tokenization and 4) transformer neural networks. It is intended to help users develop computational thinking as well as algorithmic awareness and algorithmic agency, ultimately contributing to their digital resilience in AI-driven work environments. The didactic suitability of the curriculum was tested in an AI-focused MA course at the Institute of Translation and Multilingual Communication at TH Koeln. Results suggest the didactic effectiveness of the curriculum, but participant feedback indicates that it should be embedded into higher-level didactic scaffolding - e.g., in the form of lecturer support - in order to enable optimal learning conditions.

翻译：本文提出了一套面向语言与翻译（L&T）行业的语言导向人工智能（AI）技术课程。该课程旨在通过以易于理解的方式向翻译与专业传播领域的相关方介绍现代语言导向AI的概念与技术/算法基础，培养其领域特定的技术性AI素养。课程核心内容聚焦于：1）向量嵌入，2）神经网络的技术基础，3）分词技术，以及4）Transformer神经网络。课程致力于帮助用户发展计算思维、算法意识与算法能动性，最终增强其在AI驱动工作环境中的数字韧性。本课程的教学适宜性已在科隆应用技术大学翻译与多语传播研究所开设的AI专题硕士课程中进行了测试。结果表明课程具有教学有效性，但参与者反馈指出，为创造最佳学习条件，课程需融入更高层次的教学支架——例如以讲师支持的形式——予以实施。