Complete Mastery of MS AI Core Technologies for AI Beginners

This is a course to learn Azure cloud service, a public cloud platform operated by Microsoft. Basic cloud concepts and terminology are taught by verified, experienced instructors. Core technology demonstrations are presented in their latest versions, allowing you to replicate video results. Acquire balanced theoretical and practical skills in Azure.

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.

This is a special lecture that can lay the theoretical foundation to simultaneously prepare for the Microsoft AZ-900 certification, and as the latest content reflecting the scope of questions as of May 2025, by providing content related to core data concepts, Azure's relational data, Azure's non-relational data, and Azure's analytical workloads in a form combining theory and practice, it can be utilized as a meaningful educational opportunity to not only obtain the certification but also take the first step towards becoming a data professional.

This is a course to learn AWS cloud service, a public cloud platform operated by Amazon. The basic concepts and terms related to the cloud are taught by a proven instructor with long experience, and the instructor's demonstration of core technologies is delivered in the latest version, so that you can see the same results as in the video. (Latest interface as of August 2023) Balance the theoretical and practical capabilities of AWS cloud.

The AWS Certified AI Practitioner practice exam course is a core summary program for passing the certification. First, you'll quickly review the fundamental concepts of AI/ML and generative AI, and learn about the features and use cases of AWS's major AI services that frequently appear on the exam (e.g., SageMaker, Rekognition, Polly, etc.). Based on this, you'll practice determining which AI solutions are appropriate for various real-world problem scenarios, and also cover content related to responsible use of AI models and data security. Finally, you'll learn problem-solving strategies by question type and prepare for the exam through practice mock tests. Through this course, you can efficiently prepare for the exam in a short amount of time.

A general education lecture for the public to shed the vague fear of artificial intelligence. Through concrete examples, we learn what AI learning truly means. Also, via specific examples, we examine AI's 'brain structure' and how it thinks.

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.

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.

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.

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

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.

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 :)

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.

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.

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

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.

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

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 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.

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!

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.

LLM and Agent, the fundamental technologies behind AI like ChatGPT. LLM is the technology that has come closest to AGI at this point in time. In this lecture, we explore LLM and Agent technologies from a general public perspective.

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

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.