Learning Python for Cosmology: A 30-Day Learning Journey | CosmosEdu

Welcome to CosmosEdu’s new series: Learning Python for Cosmology.

Fig1.Cosmology is data based science 


I’m Muskan Jain, an undergraduate physics student with a deep interest in cosmology. I’m starting this 30-day series because, as a beginner, I struggled to find structured and beginner-friendly resources that explain how coding actually fits into cosmology research.

So instead of waiting for the “perfect time” or the “perfect mentor,” I decided to learn Python from scratch and document the entire journey publicly — honestly, imperfectly, and step by step.

This series is not about mastering Python in 30 days. It’s about real learning: slow progress, confusion, mistakes, corrections, and gradual understanding.


Why This Series?

I didn’t have a mentor to guide me or constantly correct my mistakes. Most of my learning comes from self-study, online resources, and even AI tools. And honestly, that’s the reality for many students.

I don’t even have a personal laptop yet. I currently use my father’s laptop whenever possible. Instead of regretting what I don’t have, I chose to start with what I do have. This series is proof that you don’t need perfect resources to begin — you need courage to start.

My Passion for Cosmology

Cosmology is not just another subject for me — it’s something I genuinely care about. Through this series, I’m creating a documented archive of my learning, so that:

I can track my own growth

Other beginners can follow along

No one feels alone or “too slow” while learning

Who Is This Series For?

This series is for:

Physics students curious about cosmology

Beginners who feel coding is intimidating

Anyone who wonders how programming connects to understanding the universe

If Python feels confusing or overwhelming, you’re exactly who this series is meant for. I’ll share my confusion openly, including the days when code doesn’t run, logic feels unclear, or concepts take time to settle.

Why Focus on Coding First?

The answer is simple: every field needs tools.

Just like we need books, notebooks, and calculators to study, modern cosmology needs computational tools. Today, cosmology is a highly data-driven science. We analyze massive datasets, run simulations, and study how the universe evolves over cosmic time.

To understand phenomena like:

cosmic expansion

structure formation

dark matter and dark energy

we need programming. That’s why I’m starting this journey with Python, one of the most widely used languages in scientific research.

My Learning Approach: Study – Confusion – Reflection

Each post in this series will follow a simple and honest structure:

What I studied today

The concepts, ideas, or code I worked on.

What confused me

The parts that didn’t click immediately — for example, understanding loops or getting the correct output from my first scripts.

What I learned or corrected

Mistakes I made, insights I gained, and how my understanding improved.

This cycle helps me learn deeply and keeps my thinking transparent for readers.


Code, Notes, and GitHub

Each post will include a link to my GitHub repository, where I’ll share:

  • Code snippets
  • Practice files
  • Additional notes

This way, anyone can explore further at their own pace.

Join the Journey — Let’s Decode the Cosmos Together

This series is as much for you as it is for me.

If you’ve ever been curious about the universe but felt intimidated by dense textbooks or complex equations, I invite you to follow along. Whether you’re a student, a science enthusiast, or simply universe-curious, I hope this journey helps you take your first steps into computational cosmology.

Stay tuned for Day 1, where we’ll begin with Git and GitHub, the foundation of working with code and research projects.

Until then, keep looking up —

The cosmos is waiting to be decoded. ❤️

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