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 reopen.

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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 with smart cost-containment strategies will be the likeliest to rise above other institutions and thrive for the long term.

Outcomes:

  • Understand how AI and machine learning can help you diagnose and solve issues before they become a customer satisfaction issue
  • Learn how cloud-based architectures can dramatically reduce costs of hardware and implementation
  • Hear about the impact of microservices in the cloud on the agility of the Wi-Fi network
  • Know how AI applies to wired/wireless network and security
  • Understand how a digital network assistant with a conversational interface can quickly find and mitigate problems