Workplace Innovation in the Age of Digital Transformation (DX) and Data

Understanding AI Principles and Structure: From How AI Works to Decision-Making and Learning How does AI work, what does it base its decisions on, and how does it learn and improve? To truly understand artificial intelligence, it is important to go beyond simply using AI tools and understand the core principles and structures that make them work. This course provides a systematic explanation of AI’s operating principles, data processing and decision-making, and the mechanisms behind learning and change as part of a unified process. Rather than focusing on complex mathematical formulas or difficult programming, the course uses intuitive explanations and a variety of examples to help beginners easily understand AI’s internal structure and how it works. Through this course, you can gain a broad understanding of the process AI uses to produce results, the basis for its decisions, and how learning improves its performance. Go beyond simply using AI and build the foundational skills to understand how it works and its limitations, and to use it more effectively in your work.

Mastering difficult AI with just one single analogy?! A first step into AI principles, understanding through core concepts rather than just terminology.

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

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.

This course is structured to help even learners new to data architecture understand the material, progressing from basic data concepts → data structures and design → data modeling → databases → enterprise data architecture → AI data architecture → data architecture in practice and future strategies. In particular, it uses an online shopping company as a recurring case study to connect the foundational concepts covered in the course to real-world data design and AI applications.

Without a single formula or line of code, this penetrates the essence of basic statistics necessary for AI development and application.

1. A practice-oriented lecture designed to help you pass the AICE Associate, Korea's only nationally recognized AI certification. 2. Learn to the level of performing data analysis and AI modeling based on Python.

This is an introductory course where you learn the core concepts of Claude Code through a 3D office analogy. From hiring a single robot in an empty office, giving it a brain and a heart, equipping it with tools, permissions, and memory, to eventually having multiple robots work together as a team—each concept unfolds as an office scene. You will master every concept by interacting with the digital course materials and complete your learning through hands-on practice on your own computer.

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 :)

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.

Efficiently tackle the typical office tasks that keep employees working late—such as recurring monthly report writing and large-scale data organization—with the AI assistant Claude. Learn practical techniques for freely designing and enhancing long-form text visualizations and slides while preserving the unique formatting and layout of your company’s templates. Through this process, you can perfectly complete the manual documents that accumulate over time within the allotted deadline.

At last, I’ve gained a clear, practical understanding of the AI security review (NIS/FSI) checklists that had been somewhat ambiguously established over the past 7–8 years, and I’ve mapped out how to revise, establish, and operate the relevant management system. I’ll explain what AI security is and how it should be improved from June 2026 onward, based on the standards of Korea’s leading companies—the highest level of information security in the country. (This is not a basic introduction or conceptual overview.*) The training has been divided into PART1 (Basics_Overview) and PART2 (Advanced_Security Review), so please take a look.

< WE CAN ChatGPT ALL-IN-ONE Master Class> #Growth recipes released fresh every week #Step-by-step from the beginning, becoming your AI expert

An AI that understands Korean well, handles long documents, and even carries out real-world tasks—that is exactly the direction Solar Open 2 is aiming for. This class provides an accessible explanation of Upstage’s Solar Open 2 technical report in the order of “Introduction → Design → Training → Evaluation.” Technical terms are explained through everyday analogies and visual materials, enabling even beginners to understand “what,” “how,” and “why” as one coherent flow.

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.

An introductory AI course designed for beginners! It clearly explains key concepts, from data to generative AI. The goal is to build practical understanding—not to create AI, but to reach a level where you can ask questions and explain the concepts.

Learn how to structure diverse data—including students’ grades, school records, and areas of interest—using the AI-SPARS tool, and leverage an LLM to design everything from major exploration and college/admissions strategies to personalized roadmaps. Rather than simple Q&A, you can immediately apply in practice a systematic AX-style career and college counseling process that progresses from Profile-Interview-Major-College-Admissions Track-Gap-Roadmap-Smart Report-Portfolio.

You may have experienced Claude Code producing different results for the same request each time, violating the rules specified in its instructions, and being overly lenient in approving its own output. While developing platform servers in Pangyo and spending over $1,000 a month on Claude Code, I addressed these issues by building a harness consisting of instructions, Hooks, permissions, and a Sandbox instead of relying on prompts. In this course, you’ll build that harness from scratch, add Subagents, Agent Teams, and headless execution, and leave with a complete setup that you can copy and use as-is in other projects.

Anyone can learn data analysis with Chat GPT. You can learn how to apply it in practice through various analysis exercises. (Absolutely!! ChatGPT paid version is required!)

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