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.
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