Getting started with Deep Learning by using PowerAI – qcc10dgwpl
Course #: QCC10DGWPL
Duration: 4 Hours
This course shows students how they may quickly learn about working with data through Deep Learning (DL). Student are shown how to get hands-on experience by signing up for PowerAI free trial or free class that provides lab environments. Beginners learn how to get started with DL basics by running Jupyter Notebook. Experienced learners are shown how they may work with popular DL frameworks such as TensorFlow or try out their own practical projects within the free lab environments.
Objectives
After completing this course, you should be able to:
- Recognize the need for Deep Learning (DL) when working with data
- Summarize Deep Learning concepts and tools
- Recognize PowerAI features and advantages
- Identify PowerAI components
- Recognize DL libraries and frameworks
- Apply simple use cases for learning PowerAI
Audience
This course is for the following audience:
- Technical person interested in PowerAI
- Scientist who wants to learn about PowerAI
- Business owner who has needs for data analytics or deep learning
- Power System administrators or architects
- Power system users who work with PowerAI
Prerequisites
- General skills in commands execution and working with user interfaces are required
- Power Systems working experiences are assumed but not required
Topics
Module 1
- Lecture material: Learn to work with data and analytics
Module 2
- Lecture material: Hightlights of PowerAI features and advantages
- Reference: PowerAI product videos from youtube
Module 3
- Lecture material: Getting started on PowerAI
- Demo video: Using Jupyter Notebook examples
Module 4
- Lecture material: Verifying DL frameworks and libraries
- Demo video: Taking TensorFlow class with PowerAI lab
Module 5
- Lecture material: The PowerAI Vision Preview Technology and use cases