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Extending Networking Curriculum with Applied Artificial Intelligence

机译:应用人工智能扩展网络课程

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摘要

Artificial Intelligence (AI) and related technologies like Data Mining, Machine Learning or Neural Networks became very popular in recent years. Many IT companies today require graduated students to understand and be able to apply these technologies. Application potential of AI is not limited only to robotics, image processing or intelligent agents, but also in engineering areas like computer networking and communication. However, on most universities, networking courses focus mainly on transmission protocols, network services and hardware design only while AI, machine learning or neural networks are taught separately. This causes a gap that emerges between AI theory and engineering approach. Thus, teachers of engineering courses are challenged how to introduce their students to an application of AI in the engineering areas, e.g., electronics, communication, embedded systems, power grids, etc. This paper shows how selected AI techniques presently used in computer networks can be incorporated into networking curriculum and demonstrated to students which extends student competencies and prepares them better into future jobs. We also present two case studies where AI techniques are applied on networking data in order to solve typical engineering problems.
机译:近年来,人工智能(AI)和相关技术(例如数据挖掘,机器学习或神经网络)变得非常流行。如今,许多IT公司都要求已毕业的学生理解并能够应用这些技术。 AI的应用潜力不仅限于机器人技术,图像处理或智能代理,还包括计算机网络和通信等工程领域。但是,在大多数大学中,网络课程仅将重点放在传输协议,网络服务和硬件设计上,而AI,机器学习或神经网络则分别进行授课。这导致了AI理论与工程方法之间出现差距。因此,工程课程的教师面临着如何向学生介绍AI在工程领域(例如电子,通信,嵌入式系统,电网等)的应用的挑战。本文说明了当前在计算机网络中使用的选定AI技术如何能够被纳入网络课程并向学生展示,从而扩展学生的能力并为将来的工作做好更好的准备。我们还提供了两个案例研究,其中将AI技术应用于网络数据以解决典型的工程问题。

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