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Course Outline

Introduction

Use cases and opportunities for telecom providers

Components of AI

Computer Vision, Natural Language Processing (NLP), Voice Recognition, and more

Data as the Fuel of AI

The Role of Probability and Statistics in Driving AI

Required Programming Skills for AI

Understanding Machine Learning

Utilizing Machine Learning Libraries to Build Intelligent Systems

Data Processing Engines Underpinning Data Analysis

Decision-Making with Rules Engines and Expert Systems

Advanced Machine Learning Approaches: Deep Learning

Exercise: Predicting Network Failures Using Machine Learning

How AI Enables IoT and Its Applications in Telecom

Managing Large Data Volumes with Cloud Technologies

Automation Technologies and Strategies for Telecom

Integrating All Components

Use cases and opportunities for telecom providers (Review)

Quick Wins for Telecom Companies

Planning and Communicating an AI Strategy

Summary and Conclusion

Requirements

  • Familiarity with the telecom industry
  • Understanding of networking principles
  • General knowledge of programming concepts
 14 Hours

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Price per participant

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