Using AI and Machine Learning to Control Network Costs in Higher Education

Cost containment is a top concern for colleges and universities. Many on-campus networks are hampered by inflexible legacy architectures that require not only additional hardware to scale but manual intervention to troubleshoot and diagnose. Costs continue to rise when there is a demand for new applications, such as proximity tracing and hot zone alerting, during the pandemic or after schools re-open. The future of higher education hinges on adaptability and the use of AI and Machine Learning. Colleges and universities that embrace this reality and adapt to with smart cost containment strategies will be the likeliest to rise above other institutions and withstand for the long term.

In this webinar you will gain an understanding of:

• The application of AI and machine learning in a university network architecture can help you to diagnose and solve issues before they become and customer satisfaction issue.
• How cloud-based architectures can dramatically reduce costs of hardware and implementation
• The impact of Microservices in the cloud on the agility of the Wi-Fi network.
• How AI applies to your wired/wireless network and security. 
• The value of a digital network assistant with conversational interface to quickly find and mitigate problems.