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Course Outline
Introduction
Use cases and opportunities for Telecom providers
What makes up AI?
Computer Vision, Natural Language Procession (NLP), Voice Recognition, etc.
Data as the Oil of AI
How Probability and Statistics Drive AI
The Programming Language Skills Needed for AI
Understanding Machine Learning
Applying Machine Learning Libraries to Develop Intelligent Systems
The Data Processing Engines Behind Data Analysis
Using Rules Engines and Expert Systems to Make Decisions
Advanced Approaches to Machine Learning: Deep Learning
Exercise: Predicting Network Failures with Machine Learning
How AI drives IoT and the Applications for IoT in Telecom
Handling Greater Volumes of Data with Cloud Technologies
Automation Technologies and Approaches for Telecom
Bringing it All Together
Use cases and opportunities for Telecom providers
The Low-hanging Fruit for Telecom Companies
Planning and Communicating an AI Strategy
Summary and Conclusion
Requirements
- An understanding of the telecom industry
- An understanding of networking
- A general understanding of programing concepts
Testimonials
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