Master Course in Edge Computing 3.0

Data is collected and analyzed at the edge, rather than on a centralized server or in the cloud, using edge computing. The new infrastructure uses sensors to collect data, edge servers to process it in real-time on site, and other devices to connect, like smartphones and laptops.

Data processing needs are moving closer to the source of computation with Edge Computing. Internet of Things (IoT) networks, 5G network optimization, and the ability to offer new and enhanced mobile applications like VR are all driving this move.

There's still a place for centralized computing, like with many cloud-based services, in this move to the edge. In contrast, computing at the edge has many benefits such as reduced latency for time-sensitive data, lower capital costs, and lower operating expenses. Due to localized data processing, there's less need for backhaul infrastructure.

The five major topics I'd like to cover in this master's course are:

1. Introduction and importance of edge computing 3.0

2. Benefits, strategy, use cases, challenges, and best practices

3. Multi-access edge computing, common industry tools & implementation

4. Edge Computing in the Banking and Finance Industry

5. Edge Computing in the Manufacturing, Retail, Automobile and Healthcare Industry