The Concept of DataScience and AI (How to Study)

This course covers the basics of R programming for those who have no knowledge 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.

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.

This special lecture concurrently prepares for Microsoft AI-900 certification, featuring the latest content reflecting May 2025 exam scope, combining theory and practice, including AI overview, machine learning basics, computer vision, natural language processing, document intelligence, knowledge mining, and generative AI.

Create high-quality AI videos with Midjourney&Runway. Director Kim Dong-ah, who collaborated with Samsung, will personally guide you step-by-step through the AI video production process based on a virtual brand.

This is a course where you learn the basic calculus and PyTorch's Autograd functionality needed to get started with deep learning.

Leverage Python to learn machine learning techniques, improving real data information extraction and prediction model development skills!

AI Design Secrets to Create High-Quality Work Start Designing Right Away with Midjourney & Photoshop, Accessible to Everyone

Artificial Intelligence, AI, agents... They might seem grand, but once you try them, they're not as difficult as you think. That's why it's important to implement simple features yourself. Through practical projects that can actually be used at a company, you'll directly experience various use cases and learn how to utilize and apply AI agents.

Let's explore the types of applications or web services that can be built using LLMs.

This course covers everything from core recommendation system algorithms to practical implementation. - Content-based filtering - Collaborative filtering and deep learning-based recommendation model implementation - Two-step recommender systems implementation - Hands-on practice using PyTorch/RecBole - Industry know-how and recommendation result visualization

Conquer everything about world-changing AI in just 4 lectures! Lecture 1. The True Identity of Artificial Intelligence AI is not magic. It's a digital brain created by analyzing human 'intelligence' like a mathematical formula! We thoroughly dissect the core structure of seemingly smart artificial intelligence. Lecture 2. Algorithm, AI's Creative (?) Thinking Method How does a pondering AI find answers? Experience firsthand the strategies of AI that plays Go, finds routes, and predicts your search results. Lecture 3. AI Hardware, The Engine That Turns Imagination Into Reality! The chip inside your smartphone is the heart of AI. We dissect everything from CPU, GPU, TPU, to even those unknown names. Lecture 4. The Great Clash of Machine Learning and Deep Learning! What on earth does it mean for AI to 'learn'? From classic rule-based AI to the currently hot ChatGPT! We trace the evolution of learning.

This explains the foundational principles of large language models like ChatGPT with a focus on theory.

This special lecture lays the theoretical groundwork for simultaneous Microsoft AZ-900 certification preparation. Featuring the latest content reflecting the May 2025 exam scope, it covers cloud concepts, Azure architecture and services, and Azure management and governance, delivered with a blend of theory and hands-on practice.

In an era of explosive data growth and crucial real-time processing, edge computing has established itself as an essential technology, no longer an option. This course is designed to systematically teach everything, from the core concepts of edge computing to deployment strategies for its application in real business environments. Through this course, students will firmly solidify the fundamental principles of edge computing and acquire practical knowledge and know-how applicable to real-world tasks and projects. Take the most certain first step towards becoming an edge computing expert, a core technology in the future IT environment!

You will understand the present and future of AI technology, experience the testing process of AI models such as machine learning, and learn the role of a tester. You will comprehensively learn everything from establishing AI-based system test strategies to designing and executing test cases, and even methods for utilizing AI to support testing. This course is conducted based on ISTQB's AI Testing syllabus and provides an opportunity to perfectly prepare for the ISTQB AI Testing certification exam.

From core theories of deep learning and CNN to various CNN model implementation methods, and practical deep learning development know-how through real-world problems, If you want to become a deep learning CNN technology expert based on Pytorch, join us in this lecture :)

From Multi-Head Attention to the Original Transformer model, BERT, the Encoder-Decoder based MarianMT translation model, and even Vision Transformer, you'll learn Transformer inside and out by implementing them directly in code.

AI is no longer a tool exclusive to developers or experts. The gap between "those who use AI" and "those who don't" is already widening across all roles—from students and job seekers to office workers, planners, and developers. This course is a practical survival guide focused on: ✔️ How to use AI as a tool to explode your productivity, not as a replacement technology ✔️ Prompts you can immediately apply to work, studies, job hunting, planning, and development ✔️ The mindset that turns someone who says "I tried AI, but it wasn't that great" into an AI expert Rather than just explaining features, I will show you: 👉 What kind of people survive in the AI era 👉 Exactly how those people use AI in practice Based on my own experiences and real-world examples.

A comprehensive compilation of approximately 130 ML/AI engineer interview questions and answers learned through about 20 interviews

This is a practical, hands-on course that provides incident analysis training through practical exercises and the basic knowledge required to perform duties as a security analyst. We will together examine incident analysis methods from a practical perspective, necessary for corporate intrusion response and analysis tasks.

You can transform your ideas into beautiful presentations in just a few minutes. No more spending hours struggling with slide design. With GAMMA's AI technology, you can dramatically improve your content creation process.

Data Science(DS) & Artificial Intelligence(AI) job role analysis, plus a learning & employment roadmap for building a career in these roles.