▶ The lecture, which was recognized by leading universities/large companies, is now available online at Class 101.

Data analysis for practical use

I need to study with practical data!

▶ If you want to analyze data, use “real” data!

I thought about it every day. It's a data analysis course for practitioners, but why do they always teach only “Iris, Titanic Data”? Wouldn't it be “learning with practical data” the fastest way for practitioners to apply it to practice?

The data we encounter in practice is extremely complex. It's messy because it's unrefined, and it's very difficult to dispose of because there are many factors to consider. However, in most of the courses, lessons are conducted using data that has already been preprocessed. So even if you try to apply what you've learned to work, “How should I process the data?” When they encounter this difficulty, they give up.

The job of organizing messy data well,

It's the beginning of data analysis.

Instead of someone's well-organized Iris, Titanic, and Boston data, the training will be conducted with messy working data that you will encounter at the company tomorrow.

Customer CRM data and distribution data, which are most commonly seen in practice, are ripped off one by one and preprocessed directly. How to handle missing data, what kind of data to view, what data to combine with each other to create the desired value, etc. You will gain a deep understanding of data through a preprocessing process that you wouldn't have experienced unless it was practical data. With the preprocessing power gained through two projects, we can help you fearlessly cover over 90% of the working data you encounter.

It's not just a code-following class.

Learn data problem solving methodologies.

▶ Analysis of practical data using Python

Python lessons that only follow code cannot be used for practical work. Based on actual data, we consider “what kind of data should be combined” and “what kind of personnel should be selected” together. Follow the process of the business data analyst's project and solve the following practical exercises.

Hands-on exercises 1. Which credit card company is used the most by top customers?

Hands-on exercises 2. Distributors and shipping/receiving quantity data are managed like this!

Hands-on exercises 3. If you become a salesperson, you must do this kind of analysis!

Practical exercises 4. How many times have customers looking for a retail store visited the store?

Practical exercises 5. How do I import data from Data Base (DB)?

Practical exercises 6. How to extract data from a PDF!

Analyze with well-written code

What if it could be automated?

In practice, when you write a report or write a report, you have to go through the same process every time to process the data. In order to import large amounts of data, turn on Excel, which takes a lot of time, create functions, turn on the pivot table, and even graph.. Doing all of this in Excel takes too much time, and it's also complicated.

However, we learned Python. Organize quickly and easily by changing only the data with well-written code from the lessonTry it. You can learn how to process data easily and quickly with Python using data generated in practice.

What kind of content do you learn

How can I apply it?

1. You can learn how to process data from a practical perspective using data from actual practice (customer CRM data, distribution data).
2. Learn how to easily process data using the Python Pandas library, which is the most basic for data analysis.
3. Based on a basic understanding of data analysis, you can learn data analysis procedures for performing data analysis in practice.

A class proven by reviews,

Now it's your turn.

Learn about data analysis for practical projects with Pandas! Understand the perspective of working data and process various data at will The first step in Python data analysisLet's start with me!

If you're still not confident in the basics of Python,

Let's finish it all in one package!

If you purchase this class and [Python Fundamentals Class] together, you can take two classes at once at a 42% discount compared to the regular price. Learn all in one, from data analysis to data analysis by building a solid Python foundation with the benefits of a cheaper package.

Python basic classes that are better to listen to

We've collected only basic Python knowledge essential for data analysts. This class is recommended for those who aren't confident in Python yet, or if they want to take this opportunity to test their skills.