AI-Assisted Coding Fundamentals

This unit introduces foundational concepts and practical skills for using AI tools to support software development, including prompt engineering, AI coding assistants (e.g., GitHub Copilot, Amazon CodeWhisperer, Tabnine), and NLP-based documentation bots. Students practice automating repetitive tasks, formatting and translating code, creating test plans, debugging with AI support, and considering maintenance and ethical limitations to prepare for larger AI-enabled projects in subsequent units.

Learning Objectives

• Analyze common repetitive development and documentation tasks to identify opportunities for safe and effective automation using AI tools
• Apply prompt-engineering techniques and AI coding assistants (e.g., GitHub Copilot, Amazon CodeWhisperer, Tabnine) to generate, translate, format, and refactor code in alignment with project requirements
• Demonstrate creation of test plans, classification and resolution strategies for common bug types, and planning for the four types of software maintenance using AI-supported workflows
• Evaluate the capabilities, limitations, and ethical considerations (accuracy, privacy, licensing) of machine/deep learning and NLP-based tools and refine prompts to improve reliability and maintainability