This unit guides students to integrate AI tools across the Python development lifecycle, from ideation and prompt design to coding, debugging, deployment, and continual learning. Students will build and evaluate an OpenAI-based chatbot, apply AI code assistants and debugging platforms, and address limitations, ethics, and accessibility in AI-augmented projects.
Learning Objectives
- Analyze the capabilities and limitations of multiple AI tools (e.g., OpenAI, Claude, Codeium, Microsoft IntelliCode, Sourcery) and justify tool selection for specific Python development tasks using a comparative rubric
- Apply AI-powered code assistants and debugging platforms (e.g., Codeium, Sourcery, Bugasura, Microsoft IntelliCode) to implement, refactor, and reduce defects in a Python project, demonstrating measurable improvement in code quality or test pass rates
- Demonstrate the design, implementation, and basic deployment of a conversational chatbot using OpenAI or Claude, including prompt engineering, response filtering, and integration with a simple Python application
- Evaluate accessibility, ethical considerations, and reliability of AI outputs and create a personal professional development plan using curated resources (e.g., fast.ai, Microsoft Learn, AI4All, Gymnasium, UserWay) to sustain responsible AI-enhanced coding practices
Curriculum
- 1 Section
- 15 Lessons
- 30 hours
Expand all sectionsCollapse all sections
- Unit 4 — AI-Assisted Python Development15
- 1.1Pairing Up with AI20 mins
- 1.2Recognizing AI’s Limitations20 mins
- 1.3Developing a Chatbot with OpenAI20 mins
- 1.4Codeium20 mins
- 1.5Edabit20 mins
- 1.6Claude20 mins
- 1.7StatQuest20 mins
- 1.8Microsoft IntelliCode20 mins
- 1.9AI4All Open Learning20 mins
- 1.10Sourcery20 mins
- 1.11Gymnasium20 mins
- 1.12Bugasura20 mins
- 1.13fast.ai20 mins
- 1.14UserWay20 mins
- 1.15Microsoft Learn20 mins
Instructor
Free
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