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Prompt course · 9 lessons · 28 prompts · 1 hour · Beginner

AI for Astronomers

This prompt course for astronomers turns eight real tasks into clear AI conversations. You will draft, debug, and explain with confidence.

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What you'll learn

  • Draft research text: Turn rough results and notes into clear, submission-ready paragraphs.
  • Explain astronomy clearly: Make complex ideas clear for students, the public, and yourself.
  • Code and analyze: Get help writing, debugging, and understanding your analysis code.
  • Interpret observations: Reason about what spectra, light curves, and images are telling you.
  • Write proposals: Build a stronger science case and justify feasibility for telescope time.
  • Calibrate and troubleshoot: Plan calibrations and diagnose instrument artifacts from plots and descriptions.
  • Model and simulate: Set up and sanity-check stellar evolution and cosmic simulation work.
  • Review and share: Write structured peer reviews, confident referee responses, and prepare talks and admin.

What's inside

9 lessons · 28 prompts
  1. Before you start · framework course Break It Down: Least-to-Most, Plan-and-Solve and Tree of ThoughtsThis framework fits your astronomy work by breaking a galaxy survey analysis into subgoals, comparing methods, and planning each step before coding.
  2. Start here Priya's Thursday, two waysA day in the life of an Astronomer, before and after these prompts.
  3. 01 Lesson 1 · 5 prompts Drafting Research Text
  4. 02 Lesson 2 · 3 prompts Explaining Astronomy Clearly
  5. 03 Lesson 3 · 3 prompts Coding and Data Analysis
  6. 04 Lesson 4 · 3 prompts Interpreting Observations
  7. 05 Lesson 5 · 3 prompts Observation Proposals
  8. 06 Lesson 6 · 2 prompts Calibration and Troubleshooting
  9. 07 Lesson 7 · 2 prompts Modeling and Simulation
  10. 08 Lesson 8 · 3 prompts Peer Review and Revisions
  11. 09 Lesson 9 · 4 prompts Talks, Conferences, and Admin

About this course

7 topics

Prompts for astronomers: from data to talks

Astronomers do more than look at the sky. You write proposals, fix code, answer referees, and explain your work to many audiences. This course gives you the prompts to do those things with AI at your side.

Each lesson is short and tied to a real task. You will not learn abstract theory. You will practice turning rough notes into text, reading light curves, and preparing a talk.

  1. The lessons
    1. Drafting Research Text: Turn rough results and notes into clear, submission-ready research text.
    2. Explaining Astronomy Clearly: Explain astronomical ideas clearly to students, the public, and yourself.
    3. Coding and Data Analysis: Get help writing, debugging, and understanding the code that powers your analysis.
    4. Interpreting Observations: Reason about what your spectra, light curves, and images are telling you.
    5. Observation Proposals: Write stronger telescope proposals that make a clear science case and justify feasibility.
    6. Calibration and Troubleshooting: Plan calibrations and diagnose instrument artifacts from descriptions and plots.
    7. Modeling and Simulation: Set up and sanity-check stellar evolution and cosmic simulation work.
    8. Peer Review and Revisions: Produce structured peer reviews and confident, point-by-point referee responses.
    9. Talks, Conferences, and Admin: Prepare talks, handle Q&A, and manage the reporting side of research life.
  2. What the course covers

    The course follows eight lessons that match an astronomer's week. You start with drafting research text and end with talks and admin. In between, you learn to explain ideas, write code, interpret data, propose observations, and handle calibration and modeling.

  3. How the lessons connect

    Each lesson builds on the one before. The drafting lesson helps you write up results that come from the coding lesson. The interpreting lesson feeds into proposals. The peer review lesson uses everything you have practiced.

    You can take them in order or jump to what you need.

  4. How to use the prompts well

    A prompt is just a clear request. Give the AI context: what you are working on, what you want, and what style you need. Then read the answer with a critical eye.

    The course shows you how to ask follow-up questions and how to keep your own voice.

  5. Who it is for

    This course is for astronomers at any stage, from graduate students to senior researchers. If you write, code, observe, or teach, you will find prompts that fit. No prior AI experience is needed.

  6. Safety and privacy for this job

    Astronomy has sensitive data: unpublished results, telescope schedules, and private referee reports. The course teaches you what not to share with public AI tools.

    You will learn to use local or private options when needed and to keep your data safe.

  7. Your next step

    After the course, pick one task to try with AI each week. Start with the lesson that felt most useful. Then explore the video courses and certifications to deepen your skills.

    The goal is a steady habit, not a one-time experiment.