AI Career Readiness Quiz
13 questions · ~5 minutes · weighted 0-100 readiness score.
0/11
Technical Foundation
weight 35%Do you have programming experience?
Which programming language are you most comfortable with?
Do you understand basic machine learning concepts?
How comfortable are you with mathematics (linear algebra, calculus, statistics)?
Time & Commitment
weight 25%How many hours per week can you dedicate to learning?
What's your target timeline for transition?
Can you maintain consistency?
Financial Readiness
weight 20%Can you afford $500-2000 for learning resources?
If you need to quit your job to learn full-time, can you afford 3-6 months without income?
Motivation & Goals
weight 20%Why do you want to transition to AI?
How do you handle failure and rejection?
Personalized learning path templates
Month-by-month plans with resources, costs and checkpoints. Tap to expand.
Skills validation tests
Self-test your readiness with timed practice tests, then evaluate your portfolio.
Portfolio Project Evaluation
Self-assess if your projects are interview-ready
Checklist
Points: 10
Details: Well-organized, no junk files, clear structure
Criterion: GitHub repo is public and clean
Points: 15
Details: Problem statement, approach, results, how to run
Criterion: README is comprehensive
Points: 15
Details: Readable variable names, docstrings, comments for complex logic
Criterion: Code is clean and commented
Points: 20
Details: Not just tutorial follow-along, addresses actual use case
Criterion: Project solves a real problem
Points: 15
Details: Metrics (accuracy, F1, latency), baselines, comparisons
Criterion: Results are quantified
Points: 15
Details: Live demo link, video, or easy local setup
Criterion: Project is deployed/demo-able
Points: 10
Details: Data collection → model → deployment, not just model training
Criterion: Shows end-to-end skills
Scoring
60-74: Needs work - Improve weak areas
75-89: Good - Polish a bit more
90-100: Excellent - Interview ready
Below 60: Not ready - Significant improvements needed