Overview of Non-invasive EEG-based BMI (Motor Imagery)

This course aims to understand various security threats occurring in information systems, particularly in internet environments, and to learn core security technologies to protect against them. Focusing on key cryptographic techniques such as symmetric and asymmetric key cryptography, the course is structured to provide a systematic understanding of the overall flow of information security, including the underlying mathematical concepts of cryptography.

Students will learn the fundamentals of digital circuits, including Boolean logic, logic gates, circuit simplification, state machines, and Register Transfer Level (RTL) design. Additionally, students will learn design methods using Verilog.

You will develop the ability to define problems based on data and clearly explain the rationale and decision-making process behind them. Additionally, rather than focusing solely on the performance of a single model, you will acquire a pipeline-oriented mindset that evaluates the completeness and reliability of the entire machine learning workflow. Furthermore, you will strengthen your problem-solving skills by tracing back the causes of errors when they occur and deriving improvement directions, and through end-to-end project experience, you will acquire practical ML pipeline capabilities that can be immediately applied in real-world settings.

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.

You can enhance your development capabilities by deeply exploring the fundamental principles of large language models like ChatGPT and Claude. You will be able to learn a variety of information and development techniques that are not commonly encountered.

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

The AWS Certified AI Practitioner practice exam course is a core summary program designed to help you pass the certification. First, you will quickly review the basic concepts of AI/ML and Generative AI, and learn the features and use cases of key AWS AI services that frequently appear on the exam (e.g., SageMaker, Rekognition, Polly, etc.). Based on this, you will practice determining which AI solutions are suitable for various real-world scenarios, while also covering topics related to the responsible use of AI models and data security. Finally, you will learn problem-solving strategies for each type of exam question and prepare for the actual test through mock exams. This course allows you to prepare for the exam efficiently in a short period of time.

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

We will help those preparing for the Big Data Analysis Engineer Practical Exam with R to prepare for the exam. We will select and inform you of only the essential parts based on the questions that were on the Big Data Analysis Engineer Practical Exam. If you complete the course, you will be one step closer to passing the Big Data Analysis Engineer Practical Exam. We have reviewed the recent exam questions and uploaded related scripts and data. Also check out the latest exam information.

Students who want to learn Hadoop and Big Data will celebrate the amazing advancements in experiencing the world of Big Data through this course!

You will learn through hands-on practice everything from the basic usage of KNIME to advanced data analysis techniques, and acquire analysis skills that can be applied to actual data.

We provide an easy understanding of the concepts and principles of generative AI from a humanities perspective, including literature, film, music, and history, while exploring the cultural impacts and life changes AI will bring. We offer practical insights and strategies on how individuals and companies should respond and prepare for the AI era.

Learn machine learning techniques using Python and improve your ability to extract information from real-world data and develop predictive models!

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.

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 a replay of our fifth webinar on how to use the free data visualization tool 'HEARTCOUNT' that requires no coding. Instead of spending time learning data or learning tools, spend it finding the information you need from your data for your business.

The chemical and fine chemical manufacturing industry is a sector that requires complex processes and high safety standards. This course covers strategies for leveraging AI to increase productivity, reduce costs, and enhance safety. You can systematically learn practical skills centered on AI application cases that can be immediately applied in actual field settings, including process data analysis, quality prediction, equipment predictive maintenance, and environmental regulation compliance.

This course is ideal for those who want to focus on theory and context rather than practice, aiming to organize their knowledge of deep learning in depth and grasp the big picture. It makes the mathematical and statistical foundations of deep learning easy to understand and provides intuitive interpretations of key modern models—such as AutoEncoder, GAN, Transformer, and AlphaGo—from a developer's perspective.

This course is a hands-on program for practicing the fundamentals of machine learning mathematics and statistics using Python. While machine learning and deep learning require programming skills, a mathematical background is necessary to understand the underlying principles. Through this course, you can step-by-step master the foundational mathematics required for artificial intelligence.

The most definitive way to build the backbone of your data No more fragmented knowledge. From DAsP (Data Architecture Semi-Professional) certification to practical modeling skills, this is the single most perfectly structured masterclass. "Are you still relying on piecemeal memorization for data modeling?" The ability of an 'architect' to translate complex business requirements into clear data structures is the most irreplaceable weapon in the IT ecosystem. This course goes beyond simply passing a certification; it provides practical insights to see through the enterprise-wide data flow.

Analyzing customers, markets, and revenue patterns—you no longer need to learn it yourself. Just ask AI, and expert-level analysis and strategies are completed in an instant!

Learn a systematic approach to S&P 500 pair trading with Python. Lay the foundation for an investment strategy that excludes emotions through professional data analysis.

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.