SET 108 - Introduction to Artificial Intelligence & Robotic Systems, Experimental

 
Description
This course will train students with the required skills to use artificial intelligence to solve real-world problems in robotics. Students will learn relevant linux command-line tools, editor usage, shell scripting and appropriate procedures for remotely accessing a system. They will also be introduced to the syntax and usage of TensorFlow and the concepts of GPU processing. Students will train a neural network using a library of images on a high-performance supercomputer and will deploy this network to a standalone robotic system that will be able to identify and classify objects in real-time.

1. Identify the structure and architecture of a high performance computing system, and recognize applications suited to these systems.
2. Define the main elements of a supercomputing system including and describe their impacts on performance.
3. Recognize and define the main components of artificial intelligence systems.
4. Apply common linux command line tools to remotely log in to a remote system, modify files and folders, edit configuration files, run scripts, view and kill processes and transfer information between local and remote systems
5. Explain the difference between CPU and GPU computing, and classify tasks that would be well-suited to each.
6. Prepare a set of images for use in a neural network, and perform classification, segmentation and labeling appropriately.
7. Use TensorFlow to train a neural network to recognize examples of these images
8. Deploy the neural network to a standalone robotic system.

1. Supercomputer structure and architecture
2. Linux command line tools
3. Text editors and configuration files
4. Scripts
5. Embedded & GPU Computing
6. TensorFlow
7. Image Processing
8. Neural Network Training & Deployment
9. Edge Computing Concerns

• Critical Thinking & Problem Solving
• Technological Competence

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