基于招聘数据的人工智能人才画像与培养对策

Talent Profiles of Artificial Intelligence and Its Training Countermeasures Based on Recruitment Data

挖掘招聘数据以全面洞察人工智能人才需求特征,对从过去“经验主义”的模糊教学方式过渡到“数据驱动”的精准培养方式具有重要意义。从基本资历、专业知识、工具技能和能力素质4个维度构建人才画像模型,并采集人工智能9个热点领域网络招聘数据挖掘人才需求特征进行实证分析。总体而言,人工智能热点领域雇主最看重的能力素养是雇员的实践经验是否丰富。具体来看,对基础研究型人才的要求更侧重于英语使用能力和论文发表能力;应用实践型人才需要掌握更多的电子、语音识别和计算机软硬件处理等相关专业知识;技术研发型人才更偏向于可以熟练搭建算法框架、进行模式识别及处理自然语言。此外,对基础研究、应用实践人才的专业需求颇为相似,而对技术研发人才的需求相对较为复杂,3类人才工具技能需求以编程语言和机器学习居多。根据研究结果,提出实施分层差异化人才培养模式、培养人工智能复合型人才、注重素质教育与通识教育、引入优秀社会人才授课和搭建人工智能知识共享平台等建议。

Mining recruitment data to fully understand the characteristics of artificial intelligence talent needs is of great significance to the transition from past“empirical”teaching to“data-driven”precise training.A talent profile model was constructed from the four dimensions of basic qualifications,professional knowledge,tool skills and abilities,and the online recruitment data in nine hot areas of artificial intelligence was collected,and an empirical analysis was made on the characteristics of talent demand.In general,the most important competency for employers in AI hotspots is whether employees have rich practical experience.Specifically,the requirements for basic research talents focus more on the ability to use English and the publication of papers;the practical talents need to master more related professional knowledge such as electronics,speech recognition,computer software and hardware processing;technical R&D talents prefer to be proficient in building algorithm framework,pattern recognition and natural language processing.In addition,the professional needs of basic research and application practice talents are quite similar,while the needs of technical R&D talents are relatively complex.The tool skills of the three types of talents are mostly in programming language and machine learning.According to the research results,some suggestions were put forward,such as implementing hierarchical and differentiated talent training mode,deepening the cooperation between industry,university and research,cultivating compound talents of artificial intelligence,paying attention to quality education and general education,introducing excellent social talents to teach,and building artificial intelligence knowledge sharing platform.