The requirements for high-quality, reliable, predictable software becomes increasingly necessary as its use continues to grow—both generally and in mission- or life-critical environments, as well as in the latest AI technology. As the software industry evolves, the need for qualified engineers trained in the principles, methodologies, techniques and tools of software quality assurance, software ethics, and data model accuracy for AI has also grown. This course presents the specifics of software quality assurance and software testing. The course also describes how these processes fit into the software development process, how ethics apply to software engineering and how software models are developed for AI.

Learning Outcomes
At the conclusion of the course, you should be able to

• Identify critical processes that instill quality assurance in the SW development life-cycle
• Focus on Verification activities within software development
• Explain various validation methodologies
• Describe concepts of ethics related to AI and SW Engineering
• Understand test tools
• Understand SW Test terminology
• Write a successful Systems Test Plan
• Develop a Traceability matrix