Skills You’ll Learn

Basic statistical theory

It deals with the statistical theory required for data analysis.

Regression analysis and predictive modeling

It deals with methods for statistical modeling using given data.

Advancement of predictive modeling

It covers the points to be aware of and know-how in predictive modeling.

Machine learning and text data processing

It covers machine learning and text data analysis methods for analytical versatility.

Class introduction

[100% student satisfaction! Once you've learned the basic grammar of R and the overall concept of data analysis through [R Data Analysis Starting from the Basics - Introduction], let's go one step further through the intermediate course. We have prepared an intermediate class to improve R data literacy through predictive modeling, text mining, etc.

Course effect

In addition to structured data, you can also learn how to deal with unstructured data.
You can create data analysis reports that reflect the content of statistics and machine learning.
Instead of just copy/pasting code, you can improve your computational thinking by writing and learning to code together.

Recommended target

Those who want to learn more in-depth data analysis
Those who want to analyze data using R - Everyone who wants to learn statistics and machine learning
Graduate students who have trouble writing papers using R data analysis - Those who want meaningful statistical verification

Pre-course notes

Course environment: Windows or Mac does not matter
Program used: R Studio
Prior knowledge: You must know basic R grammar. (dplyr, ggplot2, and reshape libraries can be used)
If you don't have enough basic R grammar, we recommend that you take an introductory class in advance.

3 reasons why this class is special

Lectures incorporating vivid experiences

I incorporated all of my experience in 1) more than 100 lectures, 2) data analysis and development practices experienced at the company, and 3) my experience through doctoral programs in statistics and industrial engineering into the class. With proven teaching skills that reach 100% student satisfaction, we will guide you on the best path so that you can quickly learn only the content you need for practical work.

Step by step roadmap for 'Beginner - Intermediate-Advanced'

1. introductory

Based on an understanding of data analysis processes and processes, you will learn data preprocessing and visualization techniques using R The final step is to create data analysis reports and dashboards.

2. Intermediate (current level)

You will conduct modeling for predictive analysis based on statistics for practical data analysis, and learn machine learning to advance it.

3. Advanced (coming soon)

It focuses on practical project handling techniques based on elementary and intermediate courses. Learn various analytical techniques, including unstructured data, and develop skills to handle data freely.

Curriculum that captures both theory and practice

The curriculum is structured by arranging theory and practice in a balanced manner based on well-structured textbooks written by myself. In addition to simply learning theory, students learn the entire process of data analysis by examining examples used in practice in order and conducting theory and practice together.

< Practical example of writing an analysis report >

< Examples of course materials >

< Data visualization Lab examples >

< Machine learning practice examples >

Class Kit · Coaching Session

💌 1:1 coaching directly taught by DoubleKPark (DoubleKPark)

You can ask 2 questions per coaching ticket.
We will write an answer of around 300 characters per question and send it to you.
A coaching ticket is a system that helps you with questions if you have a difficult part while listening to a lecture.

1 ️ Data analysis job portfolio consulting

We provide consulting on job turnover, employment, and future directions.

2 ️ Project advice

We can advise on company projects, contests, and personal projects. Please ask the following 5 questions.
Project name/Field/Progress/Problems/Questions

3 ️ Class-related questions

We will explain the exercise code related to the class, explain additional content, and correct the code.

In addition to this, if you personally want 1:1 coaching, we will help you to the extent that we can deliver answers.
Coaching answers are based on the date questions are received, and answers are provided sequentially. Responses can take up to 1 week.
The coaching ticket can be used for 20 weeks from the date of purchase.
If not used within the period, no refund will be given.

📌 For inquiries about product defects or incorrect delivery, please contact the Class 101 Customer Service Center.

📩 The kit is subject to some changes, and we will be fully informed if there are any changes.

Curriculum

Creator

Doublekpark

Hallo I go to a data analysis company and I'm currently studying for a doctorate in search of freedom at Doublekpark.

Present) Data Science & Engineering Ph.D. Program
Present) More than 100 tutoring platforms, data analysis & R lessons
WRITING 'MUST LEARNING WITH R' WRIQUEDOX
Wikibooks published “Learning Data Analysis with R through Practical Projects”

In '17, I accidentally saw an advertisement on a broadcasting platform and asked, “Shall I try it too?” I'm still doing data analysis and R lessons that I started thinking about. For me, it's important to earn money from lessons, but what I thought was important without missing out on that is “interaction with students.”

In addition to just the hard work of the lesson, the lessons were conducted with the importance of sharing experiences and thinking about things together through conversation. Therefore, there were a lot of one-on-one lectures, and I think I had the opportunity to meet a lot of nice people because of this.