10 questions · need 7/10 to pass.
Q1. When applying "The 30-day challenge: one track per day (or how to actually start)" in practice, which of these holds?
single
A The rest of this course teaches craft — prompt structure, arrangement discipline, mix/master with human ear — so your outputs don't fall into the slop pattern. B Suno and Udio dominate full-song generation (vocals + instruments in a single prompt); MusicGen and Stable Audio are the go-to open-weights options for instrumentals; ElevenLabs owns AI voice/vocals (spoken + increasingly sung); Riffusion and YuE handle style transfer + remixes; MusicLM by Google exists but rarely wins on quality. C At day 30 you'll have 30 tracks, a personal genre-affinity picture, a working sense of prompt iteration, and a taste ceiling you can hear moving. D (Depends on state, artist agreement, and platform.) This task gives you the current 2026 lay of the land — updated to reflect the RIAA lawsuits, the Anthropic settlement, and the EU AI Act rulings — so you don't accidentally publish something that gets pulled or triggers a claim.
Q2. Which statement about how "Your workflow choice: generate-and-curate vs. stem-by-stem" actually works is correct?
single
A At day 30 you'll have 30 tracks, a personal genre-affinity picture, a working sense of prompt iteration, and a taste ceiling you can hear moving. B **Stem-by-stem**: generate individual instrument stems (bass in Stable Audio, drums in MusicGen, vocals in ElevenLabs, pads elsewhere), layer them in a DAW, mix like a real producer. C Suno and Udio dominate full-song generation (vocals + instruments in a single prompt); MusicGen and Stable Audio are the go-to open-weights options for instrumentals; ElevenLabs owns AI voice/vocals (spoken + increasingly sung); Riffusion and YuE handle style transfer + remixes; MusicLM by Google exists but rarely wins on quality. D Six things need to be open and coordinated: (1) the AI tool's browser tab, (2) your reference library, (3) a scratch notes doc for prompt iterations, (4) your DAW if stem-by-stem, (5) a 'done' folder on disk for keepers, (6) a metronome or tempo reference.
Q3. For "The AI slop track trap: what makes AI music sound like AI", which detail or constraint from the module is accurate?
single
A The rest of this course teaches craft — prompt structure, arrangement discipline, mix/master with human ear — so your outputs don't fall into the slop pattern. B Every AI prompt session, you'll pull a reference track from this library and prompt 'in the vein of X but with Y different' — this reference-driven prompting produces dramatically better results than vibes-based prompting. C (Depends on state, artist agreement, and platform.) This task gives you the current 2026 lay of the land — updated to reflect the RIAA lawsuits, the Anthropic settlement, and the EU AI Act rulings — so you don't accidentally publish something that gets pulled or triggers a claim. D You don't need a degree in music theory to make good AI music, but you do need vocabulary — the exact words that make prompts land.
Q4. "Your listening reference library: pick 20 tracks" — which of these claims is supported by the module?
single
A At day 30 you'll have 30 tracks, a personal genre-affinity picture, a working sense of prompt iteration, and a taste ceiling you can hear moving. B **Stem-by-stem**: generate individual instrument stems (bass in Stable Audio, drums in MusicGen, vocals in ElevenLabs, pads elsewhere), layer them in a DAW, mix like a real producer. C Six things need to be open and coordinated: (1) the AI tool's browser tab, (2) your reference library, (3) a scratch notes doc for prompt iterations, (4) your DAW if stem-by-stem, (5) a 'done' folder on disk for keepers, (6) a metronome or tempo reference. D Every AI prompt session, you'll pull a reference track from this library and prompt 'in the vein of X but with Y different' — this reference-driven prompting produces dramatically better results than vibes-based prompting.
Q5. Which definition of "The AI slop track trap: what makes AI music sound like AI" matches what the module established?
single
A Ninety percent of AI-generated music sounds AI-generated in a specific, avoidable way: over-compressed, texturally muddy, structurally repetitive, lyrically clichéd ('neon dreams, digital hearts, electric souls'), vocally auto-tuned to death, mixed too loud, and ending exactly on the beat with an unearned crescendo. B Two workflows dominate serious AI music production. C Before you generate anything, you need a personal reference library — 20 tracks you love, with specific notes on WHY. D You don't need a degree in music theory to make good AI music, but you do need vocabulary — the exact words that make prompts land.
Q6. Which of these correctly identifies the role of "The 2026 AI music landscape: Suno, Udio, MusicGen, Stable Audio, ElevenLabs" in the broader system?
single
A The AI music tooling landscape in 2026 has consolidated around a handful of workhorses. B Before you generate anything, you need a personal reference library — 20 tracks you love, with specific notes on WHY. C Ninety percent of AI-generated music sounds AI-generated in a specific, avoidable way: over-compressed, texturally muddy, structurally repetitive, lyrically clichéd ('neon dreams, digital hearts, electric souls'), vocally auto-tuned to death, mixed too loud, and ending exactly on the beat with an unearned crescendo. D You don't need a degree in music theory to make good AI music, but you do need vocabulary — the exact words that make prompts land.
Q7. Which statement about how "The 2026 AI music landscape: Suno, Udio, MusicGen, Stable Audio, ElevenLabs" actually works is correct?
single
A The rest of this course teaches craft — prompt structure, arrangement discipline, mix/master with human ear — so your outputs don't fall into the slop pattern. B Suno and Udio dominate full-song generation (vocals + instruments in a single prompt); MusicGen and Stable Audio are the go-to open-weights options for instrumentals; ElevenLabs owns AI voice/vocals (spoken + increasingly sung); Riffusion and YuE handle style transfer + remixes; MusicLM by Google exists but rarely wins on quality. C (Depends on state, artist agreement, and platform.) This task gives you the current 2026 lay of the land — updated to reflect the RIAA lawsuits, the Anthropic settlement, and the EU AI Act rulings — so you don't accidentally publish something that gets pulled or triggers a claim. D You don't need a degree in music theory to make good AI music, but you do need vocabulary — the exact words that make prompts land.
Q8. For "Setting up your first session: browser tabs, DAW, notes", which detail or constraint from the module is accurate?
single
A The rest of this course teaches craft — prompt structure, arrangement discipline, mix/master with human ear — so your outputs don't fall into the slop pattern. B At day 30 you'll have 30 tracks, a personal genre-affinity picture, a working sense of prompt iteration, and a taste ceiling you can hear moving. C Six things need to be open and coordinated: (1) the AI tool's browser tab, (2) your reference library, (3) a scratch notes doc for prompt iterations, (4) your DAW if stem-by-stem, (5) a 'done' folder on disk for keepers, (6) a metronome or tempo reference. D Suno and Udio dominate full-song generation (vocals + instruments in a single prompt); MusicGen and Stable Audio are the go-to open-weights options for instrumentals; ElevenLabs owns AI voice/vocals (spoken + increasingly sung); Riffusion and YuE handle style transfer + remixes; MusicLM by Google exists but rarely wins on quality.
Q9. Which fact about "What music theory you actually need (and what you can skip)" matches the mechanism the module covered?
single
A You don't need a degree in music theory to make good AI music, but you do need vocabulary — the exact words that make prompts land. B **Stem-by-stem**: generate individual instrument stems (bass in Stable Audio, drums in MusicGen, vocals in ElevenLabs, pads elsewhere), layer them in a DAW, mix like a real producer. C Every AI prompt session, you'll pull a reference track from this library and prompt 'in the vein of X but with Y different' — this reference-driven prompting produces dramatically better results than vibes-based prompting. D Six things need to be open and coordinated: (1) the AI tool's browser tab, (2) your reference library, (3) a scratch notes doc for prompt iterations, (4) your DAW if stem-by-stem, (5) a 'done' folder on disk for keepers, (6) a metronome or tempo reference.
Q10. When applying "Copyright + platform policy: what you can (legally) publish" in practice, which of these holds?
single
A **Stem-by-stem**: generate individual instrument stems (bass in Stable Audio, drums in MusicGen, vocals in ElevenLabs, pads elsewhere), layer them in a DAW, mix like a real producer. B You don't need a degree in music theory to make good AI music, but you do need vocabulary — the exact words that make prompts land. C Every AI prompt session, you'll pull a reference track from this library and prompt 'in the vein of X but with Y different' — this reference-driven prompting produces dramatically better results than vibes-based prompting. D (Depends on state, artist agreement, and platform.) This task gives you the current 2026 lay of the land — updated to reflect the RIAA lawsuits, the Anthropic settlement, and the EU AI Act rulings — so you don't accidentally publish something that gets pulled or triggers a claim.