Understanding the latest big data and artificial intelligence trends

Are you feeling stuck trying to implement an agent that goes beyond a simple chatbot? Based on my own trial and error and know-how from official documentation, I will show you how to build intermediate-level agents that can be immediately applied to real-world tasks.

Understand the operating principles of generative AI models using deep learning and acquire practical application skills through hands-on exercises.

Recently, all the remarkable achievements in the field of artificial intelligence are being announced in the area of reinforcement learning. This covers reinforcement learning technology—which is bringing about true innovation in AI such as robotics, autonomous driving, and humanoid machines—from basic to advanced levels in an easy-to-understand way for beginners.

Do you know the basics but feel stuck when it comes to practical application? I will clearly break down complex LLM structures by incorporating real-world industry experience.

Simple tutorials alone make it difficult to apply in practice. I will clearly pass on my professional know-how, covering complex state management and multi-agent design methods.

Are you feeling stuck on how to apply what you've learned to real-world tasks even after mastering the basics? I will help you complete complex RAG and agent designs using my professional industry know-how.

Do you want to take your first step into the world of data? Learn machine learning and deep learning, the core technologies of AI, with Python. This course will guide you step by step, from the basics of machine learning and deep learning to practical applications. Traditional machine learning and deep learning are based on many of the same principles and technical systems. Therefore, this course does not separate the two into separate subjects, but rather organizes them into one connected course so that beginners can increase their understanding of machine learning as a whole.

Are you feeling overwhelmed by practical application and interview preparation? Based on my industry experience, I will help you firmly grasp everything from CNN to DETR, with a strong focus on code.

This course covers everything from the basic concepts of recommendation systems to the principles of applying deep learning. Develop your practical skills for recommendation service development by learning various recommendation algorithms, including collaborative filtering, content-based filtering, and hybrid recommendation systems!

Time is constantly flowing, and data is constantly accumulating. In this dynamic world, time series data plays a vital role in every aspect of our lives. From the volatility of financial markets to subtle signals of climate change, time series data captures it all. Now learn how to interpret and leverage this powerful data using the power of Python and deep learning!

You can acquire an overview of machine learning and deep learning, how to use basic tools, and the Python language knowledge necessary for learning in a short period of time.

Do you know the theory but feel lost when applying it to real-world data? I will pass on practical techniques to solve complex fraudulent transactions directly with code, incorporating my professional know-how.

Basic knowledge is not enough for real-world investing; build your own profit model using the machine learning know-how of a 10-year veteran quant.

Learn how to build deep learning models yourself using intuitive and Pythonic PyTorch. This reflects the latest PyTorch version.

Are you new to coding or looking to take your coding skills to the next level? This course will introduce you to Python, a powerful and flexible language, designed for all levels of learners. Taught in a “follow-along” fashion, this course will allow you to learn by actually writing and running code. You’ll discover why Python is one of the most popular programming languages. From artificial intelligence to web development, learning the Python language offers endless possibilities, and it’s an opportunity to greatly expand your personal potential.

JavaScript, which is known to all web developers, now explore the world of machine learning with this powerful language! This course learns how to build and deploy machine learning models using JavaScript and the powerful machine learning library Tensorflow.js. It guides you step-by-step through all the technologies required to develop web-based machine learning applications. Through this course, learners will systematically understand the core principles of machine learning. In addition, you will learn how to develop deep learning models using JavaScript and Tensorflow.js APIs, how to utilize transfer learning based on pre-trained models, and how to apply all this knowledge interactively in a browser environment.

Through this lecture, you'll be able to learn about the AI graduate school admission process and preparation methods from start to finish! I'll also share some great tips to increase your chances of getting accepted!

You can benchmark manufacturing innovation methods for semiconductors and run machine learning and deep learning with semiconductor data without coding.

**"AI Philosophy - Ethics and Challenges in the Age of Artificial Intelligence"** is a topic that deals with the ethical and philosophical exploration of the development of artificial intelligence (AI) and its impact on human society and culture. This topic goes beyond simple technological development and delves into how AI affects human life and what ethical decisions we should make accordingly.

An introductory AI lecture tailored for those new to artificial intelligence! It easily summarizes core concepts from data to generative AI. The goal is not to build AI, but to achieve a level of practical understanding where you can ask the right questions and explain the technology.

[The 2nd edition is scheduled for completion in 2026] You can develop your programming skills while exploring the fundamental principles of Large Language Models (LLMs) such as ChatGPT and Claude in depth. You can learn a variety of information and development techniques that are often difficult to come by.

Customer analysis completed with Excel and Orange, from cross-selling to A/B testing and churn risk management all at once

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.

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!

This course covers the entire process of evolving ChatGPT from a simple conversational AI into an intelligent AI Agent that performs real-world tasks. By utilizing the three core frameworks—LangChain, LangGraph, and LangSmith—you will build AI Agents that can be used immediately in practice.

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

Based on over 100 deep learning training sessions, this course systematically organizes the core foundational theories that students found most challenging. The course connects mathematical intuition, model learning principles, and code implementation step by step in a way that even non-majors can understand, deeply covering the fundamental structure and operating principles of how AI models learn, rather than just library usage. This is a practical introductory course designed to help you grow into a skilled engineer who understands AI principles by implementing core deep learning foundational technologies such as gradient descent, loss functions, optimization, perceptrons, multilayer neural networks, and backpropagation through both formulas and code.

Using block coding Entry, foster computational thinking and problem-solving skills, and through Entry AI tools, learn artificial intelligence concepts and practice simple machine learning.

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 gain a broad range of knowledge, from establishing AI-based system testing strategies to designing and executing test cases, as well as utilizing AI for test support. This course is based on the ISTQB AI Testing syllabus and provides an opportunity to perfectly prepare for the ISTQB AI Testing certification exam.

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.

This course is a hands-on masterclass that completely conquers the evolution of Diffusion Models through papers and code implementation. You'll learn the core models of generative AI, including DDPM (Denoising Diffusion Probabilistic Model) and DDIM, by studying the paper principles and implementing them directly. We analyze step-by-step the background of each model's emergence, mathematical formulations, network architectures (U-Net, VAE, Transformer), training processes (Noise Schedule, Denoising Step), and the ideas that led to performance improvements. Students will directly code all models using PyTorch, gaining not just paper comprehension but 'practical skills to reproduce and apply' them in real-world scenarios. Additionally, by comparing the differences between models and their developmental flow, you'll clearly understand how they expand and evolve. This course integrates theory, code, and practice into one comprehensive journey, providing researchers, developers, and creators alike with a systematic way to master the evolution of generative models. Beyond simply 'reading' papers, start your experience of 'understanding and recreating' through direct implementation now.

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.

The Master Guide to AI for Java Developers! This course shatters the prejudice that AI is the exclusive domain of Python and empowers your Java applications with AI-driven eyes, ears, voice, and even coding capabilities. Grow into an AI Architect based on the OpenAI API. You will directly develop various AI experts such as an AI writer, translator, artist, and coding companion. You will also build a multi-functional AI assistant that integrates core features including text summarization, sentiment analysis, image description, Java code generation, speech-to-text/text-to-speech conversion, and image/subtitle generation. This is a golden opportunity to maximize the competitiveness of existing Java systems by learning how to assign AI roles through system messages and even implement harmful content moderation.

This is an introductory lecture designed to help you understand the core concepts of non-invasive EEG-based Brain-Machine Interfaces (BMI) and the process of Motor Imagery-based signal processing. It provides an easy-to-follow explanation of the entire workflow, from the basic principles of EEG signals to Motor Imagery experiments, data processing, and how actual BMI systems operate.

This is a practical course where even beginners can learn how to quickly create PDF and Notion templates using AI and generate passive income by selling them on platforms like Etsy, Gumroad, and the Notion Marketplace. You will master everything at once, from market research and production to creating product detail pages, uploading, and sales strategies.

In the era of AI, developers must become "integrators" rather than mere coders. This course covers how to combine Unreal Engine with the latest AI tools like ChatGPT and Claude into the actual C++ development process. Through practical examples designed by Unreal Authorized Instructor YAL, you can build a development environment where AI generates, analyzes, and assists with code, completing a next-generation C++ workflow that integrates AI and Unreal.