We believe that as AI continues to advance and automate what has historically been human work, your domain knowledge is what actually sets you apart. AI is as effective as the combination of its underlying capabilities and the instructions you give it. Good directions unlock more of what the model already knows. So, it performs best when you speak the exact technical language, frameworks, and logic of the field you're in. Deep fundamentals aren't being replaced; they are your superpower for writing high-level prompts and auditing complex outputs. To build a solid career in tech, you should periodically audit your own skill readiness as the problems you target and concepts you'll apply increase in complexity. We created this course as the first readiness check in your journey to become a high-impact AI-native software engineer.
This self-paced course helps learners with foundational Java experience assess their preparedness for AI-assisted software development through guided diagnostics, practical exercises, and structured software evaluation activities.
Through the course, learners will practice:
- Evaluating AI-generated code for correctness and quality
- Strengthening Java programming and debugging foundations
- Applying structured prompt engineering techniques
- Identifying hidden bugs and unsafe software patterns
- Detecting technical debt accumulation and misleading fixes
- Verifying software behavior through testing and reasoning
- Applying tests-first thinking to AI-assisted workflows
Activities include code critique labs, prompt refinement exercises, software reasoning tasks, and an end-to-end AI-assisted development workflow.
Model solutions and readiness rubrics are provided throughout the course so learners can compute a personalized readiness profile and identify areas for future growth.
This course emphasizes critical evaluation, verification, and software reasoning to support effective and responsible use of Generative AI in software development.
