Building the Basics of R Programming

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.

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.

A course for DS/AI beginners aiming to study. It will explain DS/AI concepts and fields, guiding what and how to study.

This is a lecture for non-majors or high school students who are studying data science and artificial intelligence for the first time. We will teach you the concepts of artificial intelligence and machine learning and what efforts you need to make to get a related job.

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!

Theory and practice are different. We will understand the basic concepts of machine learning and introduce the core concepts and theories of various models that you must know. And we will share various techniques and know-how that are helpful in practice while handling various data.

This is a PDF textbook that covers the basic grammar of R, frequently used functions, and useful intermediate to advanced techniques.

This course is for those who want to study machine learning but lack statistical knowledge.

This course covers basic natural language processing techniques and various text tasks using deep learning.

Learn how to collect and manage all stocks listed on the stock market. Create a dashboard using shiny that automatically collects new stock prices every day and can also identify stock trends by industry.

Learn about GAN (Generative Adversarial Networks) in an easy and accurate way.

Learn MLP, CNN, and RNN, the basic framework of deep learning, quickly and easily.

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.

This is a lecture that teaches you how to do data science through R. You will learn line by line, from loading data to building models and model performance strategies.

We cover frequently used functions for R programming, how to write code efficiently, and intermediate techniques.

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.

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!!

I will make it so that you can crawl freely. Most of the lectures are conducted through live coding. Please follow along line by line while I code!

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

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.

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.

We cover frequently used functions for R programming, how to write code efficiently, and intermediate techniques.

Master the Big Data Analysis Engineer certification, an essential but never easy-to-self-study credential, in a short period by utilizing R, an easy-to-learn data analysis tool!!

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 course on the R program, which is widely used in statistics and data analysis. It covers everything from a basic introduction to the program to intermediate-level statistical theory and modeling.

We are going on a long journey into the unknown world of deep learning and artificial intelligence. Let's leave complex formulas and coding behind for a moment and set off with the wings of R and Keras.