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  • Course Length:
  • 4 hours

In the age of Automation and Artificial Intelligence, Machine Learning, or ML, has become the dominant AI approach. This course provides an overview of what ML and Deep Learning are and how they are used within the telecom industry. A high-level description of the main types of models used in ML (i.e., Feed Forward, Convolutional Neural Network, Long Short Term Memory, etc.) and the use cases where they are proven valuable is discussed. Overview of the training process is also explored. The course concludes with practical examples demonstrated to see ML in action.

A high-level technical overview to personnel involved in product management, marketing, planning, design, engineering, and operating wireless (4G, 5G) and wireline access networks

After completing this course, the student will be able to:
■ Describe Machine Learning and Deep Learning
■ Describe Model Building
■ Explain how a model learns
■ Compare various Machine Learning Models

1. Machine Learning and Deep Learning
1.1 Machine Learning Defined
1.2 Types of Learning
1.3 ML Lifecycle

2. ML Model Building
2.1 Types of Models
2.2 Key Parameters in Building
2.3 Models and Data
2.4 ML and Hardware

3. ML Model Training
3.1 What are we training?
3.2 Success Criteria
3.3 Training Parameters and Time

4. ML Models Compared
4.1 Key Types of ML models
4.2 ML Model Use Cases