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The easiest explanation of R-based data visualization📊. (Almost) everything you need to know😎. At the end, we will plot COVID-19 💉vaccine vaccination data on a map🗺️!

Master the nationally certified data analysis associate specialist qualification exam in 2 weeks! Acquire the core theories and background knowledge of data, and learn advanced knowledge of data analysis using R, a statistical analysis tool.

It lays the foundation for basic data analysis, including understanding R and data, data processing methods for data analysis, and data visualization methods. You will learn how to conveniently process data into the shape you want by utilizing variables, functions, and packages.

The way we deal with data is better approached through our visual perception than through the sense of what is more beautiful. So, it is more advantageous to understand the perceptual characteristics of data visualization than to notice them through human preferences. Therefore, through this lecture, we aim to build data analysis and graphic communication suitable for practice.

This is a practical text mining project. This is a lecture that covers everything from data collection to sentiment analysis and data visualization all at once!!

This is a lecture that will teach you step-by-step how to use R to analyze top keywords, wordclouds, sentiment analysis, and topic modeling in text.

This course is designed so that even those who are unfamiliar with statistics or are not confident in statistics can easily perform data analysis using R. Understand the basic grammar and data structure of R that can be easily overlooked, and develop your data analysis skills through various examples and practice!

A friendly R class from a professional instructor who teaches data analysis for over 1,000 hours a year! We've renewed the existing lectures and will also inform you of the latest trends.

We will learn about Q-learning and Deep Q-learning, and have time to implement reinforcement learning in R. We will cover the entire reinforcement learning content, from Deep Q-network to Self-imitation learning and Random Network Distillation.

Learn how to draw networks using R. Rather than drawing the network itself, we focus on building the shape of the data that will go into the network and how to draw the network nicely.

It covers basic data concepts, useful R functions and packages, and data analysis exercises, to allow anyone to perform big data analysis using R programming.

For those of you who are having a hard time with college statistics, a senior who was in the same position will share his know-how. Conquering basic statistics using R programming

This is a basic R programming course for beginners. Just follow along with me and type in the code twice. You will naturally become a beginner!

This is a lecture titled "Data Analysis Based on Practical Examples" prepared for data analysts.

You hear a lot from people about how important big data and data analysis are. But in reality, there aren't many places where beginners can access related knowledge. This course is a renewed lecture in 2022 based on the specialized teaching methods that have been accumulated for many years at big data professional education institutions, and teaches everything from the basics of data analysis using the R language to data visualization.

Easy and fun, with practical examples! This is a 7-day R data analysis roadmap lecture based on the contents of the book 『Getting Started with R Data Analysis』 (Hanbit Media).

You have learned the basics of programming, crawling, and text mining, but have you ever felt lost when it comes to actually doing a project? This is a lecture where you will go through a project with me from start to finish.

Build basic R programming skills and learn basic crawling techniques. We will explain each line while writing the code yourself.

Let's understand and try policy evaluation with R and R Studio!

Let's use the R language, which processes data easily and conveniently, to develop computer program utilization skills related to one's major, even for non-computer majors!