[Non-majors are very welcome] Python data analysis that even zero-base users can easily learn - Kaggle Introduction

Data analysis isn't difficult!
Learn practical data analysis with Kaggle.

Lecture Topics and Objectives 💎

1. This course covers a simple introduction to Kaggle, starting with Python data analysis .
2. The main purpose of this course is to help you approach Kaggle, which can seem difficult, from the basics step by step .
3. Gain a comprehensive understanding of how to manage your data analytics career on your own .

I highly recommend this to these people! 🔑

• Complete beginner who is new to data analysis
• Non-majors who are hesitant about where to start and what to do
• Job seekers looking to transition into data analysis

Why Kaggle? ✨

1. You can work with a vast amount of big data collected from actual corporate transactions, not data processed for educational purposes.
2. You can get high-quality data from a variety of experienced and skilled data scientists who have published their algorithms in competitions.
3. During the competition period, various new data analysis methods are born, forming data analysis trends .
4. You can often see Kaggle on job portal sites (Saramin, Job Korea).

With data analysts
Able to think about problems
Kaggle, the giant platform!

_{Image source: Kaggle}

What you'll learn in this course 🥕

• Python data analysis, statistical analysis, and machine learning
• How to learn with NumPy, Pandas, Matplotlib, Scikit-Learn, and more on Kaggle and how to participate in competitions
• Google Colab, GitHub, and Drive integration process
• How to Create a Development Blog

Lecture Features ❗️

The course is conducted with 20% theory and 80% practice.
Share links referenced by instructors to supplement any theory you may have missed and help you learn on your own.
*When referring to the link, if you are not familiar with English, please use Google Translate and Papago :)

In this lecture
Introducing the composition 📋

Check out the books by Knowledge Sharers 📖

From Python to Portfolio and Job Hunting: Unlocking Kaggle with Python (*Author's Direct Lecture)

This textbook is a guide to quickly challenge yourself on Kaggle after learning simple theories and principles of data analysis .

We introduce various stories of ups and downs that you will experience while challenging yourself in Kaggle.
It also includes how to use Github and create a Github Blog to store your job portfolio, which is just as important as challenging Kaggle.

This textbook will serve as a guide for anyone aspiring to become a data analyst.

*Purchase of textbooks is not required.

Please check before taking the class!

You can take the course with just a Google Gmail account .
However, please make sure you have enough Google Drive capacity to allow ample space for data uploads.

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