Starting My Technical Learning Blog

Welcome

Hello! I’m Soo Young Kwon, a computer science student based in Melbourne, Australia. I’m starting this blog to document my learning journey as I complete my undergraduate studies and prepare for graduate school.

Why This Blog?

I created this blog to:

1. Document My Learning: Writing helps me understand and retain what I study
2. Build a Portfolio: Showcase my technical work for future opportunities in Australia
3. Track Progress: Keep a record of my academic and personal projects
4. Share Knowledge: Contribute to the learning community

Current Situation

I’m completing a dual bachelor’s degree in Computer Science and Statistics & Data Science at Korea National Open University (KNOU) while living in Melbourne. Studying remotely has taught me self-discipline and effective time management.

This semester, I’m focusing on statistics and data analysis courses including regression modeling, data mining, and data visualization. I’m also preparing to apply for Georgia Tech’s Online Master of Science in Computer Science (OMSCS) program for Fall 2026.

What I’ll Write About

My blog posts will primarily cover:

• Statistics & Data Science: Notes and projects from my current coursework
• Data Analysis: Practical work with real datasets
• Computer Science Fundamentals: Systems, algorithms, and theory
• Study Notes: Key concepts and personal insights
• Graduate School Preparation: OMSCS application journey

Technical Background

My studies have covered:

• Core computer science: algorithms, data structures, operating systems
• Mathematics: linear algebra, discrete math, probability, statistics
• Programming: Python, R, and related tools
• Cloud computing and networking fundamentals

Goals for This Blog

For the next year, I plan to:

• Post regularly about what I’m learning
• Document projects with clear explanations
• Build a comprehensive portfolio
• Connect with the tech community in Australia

Example: Simple Data Analysis in Python

Here’s a basic example of the kind of work I’ll be sharing:

import pandas as pd
import matplotlib.pyplot as plt

# Load and explore data
df = pd.read_csv('sample_data.csv')
print(f"Dataset shape: {df.shape}")
print(df.describe())

# Basic visualization
plt.figure(figsize=(10, 6))
plt.scatter(df['x'], df['y'], alpha=0.5)
plt.xlabel('Feature X')
plt.ylabel('Target Y')
plt.title('Exploring the Relationship')
plt.show()

This is just a starting point - future posts will include more detailed analyses and methodologies.

Looking Ahead

I’m excited to share my learning journey. Whether it’s a challenging regression problem, a data visualization project, or notes on computer systems, I’ll document it here.

If you’re on a similar path or working in tech in Australia, I’d love to connect!

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Coming soon: A detailed post on my regression modeling coursework and practical applications.