A skills-versus-roles self-assessment
Edit the mine ratings to match yourself and rerun. The role profiles are illustrative, not data.
What three AI-era roles do day to day, which skills from this course each one uses most, and what to learn after it, with the Hectal courses that already exist and the ones that are planned.
Change the code and press Run (Ctrl+Enter). Predict what will happen first, then break it on purpose and read what changes. Your edits are saved and match the lesson page.
Ready for more? This phase has 6 hands-on exercises with automatic checks.
Practice questions
Write the code in the editor, run it, then open the model answer to compare.
Write a function coverage(profile, mine) returning the percentage (0 to 100, rounded to one decimal) of a role's required points that you cover.
Write a function biggest_gaps(profile, mine, n) returning the n skills with the largest shortfall, largest first, ties alphabetical.
Use graphlib to print a valid learning order for three topics where b needs a and c needs b.
Explain it without notes
Describe the day-to-day work of an AI engineer and which Python skills it uses most.
How does a forward deployed engineer's work differ from an AI engineer's?
What do AI scientists do that engineers usually do not, and what should they learn next?
Which skills are shared by all three roles?
Expected output
AI Engineer: 10/20 points covered (50%)
biggest gaps: async (+2), prompts (+2), systems (+2)
Forward Deployed Engineer: 8/17 points covered (47%)
biggest gaps: communication (+3), systems (+2), apis (+1)
AI Scientist: 7/16 points covered (44%)
biggest gaps: experiments (+3), data (+2), math (+2)