[Certification Prep] AWS Certified AI Practitioner Practice Exam Questions

This course is designed for those aiming to obtain the Data Architecture Semi-Professional (DAsP) certification. It provides a simple and systematic overview of essential exam topics, ranging from basic data architecture concepts to data modeling, data quality, and governance. The curriculum is structured to minimize complex theories and focus on frequently tested concepts, making it accessible for non-majors and beginners to learn without pressure. Build your fundamental skills in understanding data structurally while preparing for the DAsP certification.

Nationally Certified Industrial Security Manager: "Final update of the newly renewed version is complete"!! The 2026 exam schedule is expected to be announced between February and March on the following site (https://license.kaits.or.kr/license/web/board/brdList.do?menu_cd=000021). This course is designed to help you obtain the Nationally Certified Industrial Security Manager certification by providing a systematic understanding of industrial security from a management perspective. Rather than focusing on rote memorization, the content systematically organizes the concepts, structures, and flows of industrial security so that even non-security majors can understand it, preparing you for the exam while also supporting practical work and career expansion.

AI Tech DNA Series: Core Computer Fundamentals from an AI Perspective is an introductory course designed to help you understand the basic concepts of computers needed in the AI era in the easiest way possible. It explains fundamental principles such as CPU, memory, storage, networks, and data structures by connecting them to real-life analogies and AI perspectives, building a solid foundation to advance into Python, AI, security, and cloud.

[Reflecting the latest related regulations and guidelines presented by the Korea Financial Security Institute, Financial Supervisory Service, and Personal Information Protection Commission] In the rapidly changing digital financial environment, security has become not an option but a core survival strategy. This course covers the new directions of financial security changing with digital transformation, strategic response methods, and practical approaches to establishing a security culture within organizations. We will examine the policy directions of the Korea Financial Security Institute, the latest regulatory trends, and global security trends together, learning security innovation strategies centered on people and organizations beyond technology-focused approaches.

[Reflecting the latest related regulations and guidelines presented by the Korea Financial Security Institute, Financial Supervisory Service, and Personal Information Protection Commission] This is a course where you learn how an organization's security governance and internal control systems should operate through actual financial security incident cases. You will analyze the causes of incidents and response processes, and based on this, learn effective security policy establishment, risk management, and compliance response methods. The goal is to build security culture and control systems across the entire organization, going beyond technical responses.

Welcome to the R Programming Basics course! This course provides an easy and systematic guide to the core concepts of R programming and practical data handling and visualization methods for those starting out in data analysis. Starting with R installation, it covers data structures, basic syntax, and real analysis cases, aiming to help you successfully take your first step as a data analyst.

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!

What do you learn in the 'Business Information Visualization Certification' course? This certification course focuses on developing the ability to analyze data well, visualize it in an easy-to-understand way, and clearly and effectively communicate the information needed when making important decisions in a company or organization. Simply put, it's a course where you learn the skills to not just look at data, but to discover the hidden meanings within it and express them through pictures, tables, graphs, etc., so you can explain them well to others. Through this course, you will: Develop the ability to think strategically through data, build practical skills that can be immediately applied to actual work, and enhance your professional expertise and competitiveness. Through this lecture, develop the ability to connect business and data, and take one more step toward becoming an expert who understands and explains data.

This is an online course where you can learn essential content for certification, from basic concepts of information security to the latest security issues. With theory reflecting the latest exam trends and practical mock tests, you can efficiently prepare for the exam, and it's structured so that even those new to information security can easily follow along.

Computational thinking isn't something that only computer science majors learn. Every profession has problems that need to be solved, and computational thinking can be used to solve those problems.

This course is designed for those who wish to obtain the nationally certified Associate Data Analyst (ADsP) certification. At a time when there is a need to cultivate practical data analysis professionals in both public and private sectors by objectively verifying data analysis skills essential for data utilization across society, this course is structured to enable participants to develop the necessary competencies and take the qualification exam to obtain the certification.

This course is designed to help students easily understand the concepts of the Internet of Things (IoT) while simultaneously preparing for the IoT Knowledge Proficiency Test certification exam.

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.

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!

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 :)

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!

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.

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.

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

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.

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

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.

AI Utilization Master Guide for Java Developers! This course breaks the stereotype that AI is exclusive to Python, and grants your Java apps AI's eyes, ears, voice, and coding abilities. Grow into an AI architect based on OpenAI API. Directly develop various AI specialists such as AI writers, translators, artists, and coding partners, and create a multifunctional AI assistant that integrates core features like text summarization, sentiment analysis, image description, Java code generation, voice/text conversion, and image/subtitle generation. Learn to assign roles to AI through system messages and even content moderation for harmful content - this is a golden opportunity to maximize the competitiveness of your existing Java systems.

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.

This course covers the entire process of evolving ChatGPT from a simple conversational AI to an intelligent AI Agent that performs actual work tasks. Using three core frameworks - LangChain, LangGraph, and LangSmith - you'll directly create AI Agents that can be immediately used in real-world applications.

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

In the AI era, developers must become 'integrators' rather than simple coders. This course covers how to combine Unreal Engine with the latest AI tools like ChatGPT and Claude in actual C++ development processes. Through practical examples directly designed by Unreal certified 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.

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 AI Literacy and Transformation Series (1) covers the following topics: 1. Data Center Cooling Innovation in the AI Era The Problem: The explosive power consumption of the latest AI chips (GB200, etc.) has pushed traditional air cooling methods to their limits, leading to AI performance degradation and massive operational cost issues. The Solution: Presents innovative liquid cooling technologies including Rear Door Heat Exchangers (RDCH), Direct-to-Chip (DTC) cooling, and immersion cooling. Additionally, provides strategies to simultaneously secure efficiency and sustainability through intelligent control systems that predict even leakage current and circular economy models that recycle waste heat for district heating. 2. The AI Paradox: Strengthening Critical Thinking to Awaken the Brain The Problem: The phenomenon of 'cognitive offloading'—outsourcing thinking to AI—is causing modern people's analytical thinking and literacy skills to rapidly deteriorate, creating a 'cognitive debt' problem. The Solution: Redefines AI not as a simple answer tool but as a tool for a 'cognitive gym'. Builds a system that makes you think first using critique, research, and synthesis agents, and strengthens metacognitive abilities as a 'helmsman' who determines direction rather than a passive passenger. 3. AI Memory Crisis: Next-Generation Architecture Design The Problem: The size of short-term memory storage (KV cache) required by AI is exploding, but expensive and limited-capacity HBM alone faces physical limitations in handling this data wave. The Solution: Presents a strategy for building a 'heterogeneous memory dream team' combining HBM, DRAM, CXL, etc. Provides solutions that dramatically lower corporate Total Cost of Ownership (TCO) by transferring smart system architecture design capabilities that balance capacity and cost rather than focusing on single component performance. 4. Palantir Ontology: Actionable Data Intelligence The Problem: Data is overflowing but fragmented, creating a 'data graveyard' problem where it fails to translate into actual decision-making and execution, blocking corporate innovation. The Solution: Gives data context and meaning through an 'Ontology' engine that maps physical assets to digital representations. Realizes data democratization where field personnel can directly command business without IT department assistance through 'Action Types (execution capabilities)' that immediately reflect analysis results into operational systems. 5. The Great Rewiring: AI Intelligence Stack Strategy The Problem: As the technology paradigm fundamentally shifts from the Internet era's 'deterministic computation' to the AI era's 'probabilistic prediction', existing business structures are being completely shaken. The Solution: Clarifies the reality of change through a '5-layer Intelligence Stack' map connecting semiconductors to applications. Provides a strategic decision-making framework for determining whether to Build or Buy AI capabilities, drawing a roadmap toward autonomous operating enterprises. 6. Forgetful AI: Maximizing Potential Through Feedback The Problem: AI's 'catastrophic forgetting' phenomenon where learning new information causes it to forget existing knowledge, and communication problems where unilateral commands prevent AI from performing properly. The Solution: Teaches 'coaching' and example-based dialogue methods instead of commanding AI. Transfers techniques for becoming a scientific training partner that enables AI to acquire new capabilities while maintaining existing knowledge through gradual feedback techniques that minimize behavioral change shock (KL divergence). 7. Engineering Financial Intelligence The Problem: Financial systems that remain stuck in past bookkeeping records and regulatory compliance cannot optimize capital allocation for an uncertain future. The Solution: Transforms into a 'dynamic scenario planning (war game)' system that computes thousands of variables in real-time using generative AI. Helps CFOs evolve beyond simple managers into strategic architects who design corporate value through 'Financial LLM' utilization methods that convert simple numbers into strategic signals.

An introductory AI lecture tailored for those new to AI! Key concepts, from data to generative AI, are simply explained. The goal is practical understanding, enabling you to question and explain AI, not build it.

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.