Discover how machine learning is used to forecast network congestion, predict failures, and anticipate customer churn.
We will break down the three core types of ML: supervised, unsupervised, and reinforcement learning, with a focus on their practical telecom applications.
A dedicated module shows how ML algorithms dynamically allocate resources to directly optimize and maximize user throughput.
The course details the tangible benefits of ML, including enhanced network performance, reduced operational costs, and proactive fault management.
You will learn how these technologies enable the transition from reactive maintenance to predictive optimization.
This course provides the foundational knowledge to leverage AI for building smarter, self-optimizing telecommunications networks.