The Current State of AI Development as Felt Through Meeting with Numerous AI Companies

The best introductory programming course that has already been taken and enjoyed by over 20,000 people. This introductory programming course was planned and prepared by Inflearn from the perspective of a non-major, and helps people who have never touched programming before to develop programming skills that can be used in real life.

Based on basic Python grammar knowledge, we will gradually increase the difficulty level from easy to difficult examples. During this process, you will learn how to study on your own, acquire solid grammar knowledge, and firmly establish your basics. In addition, we will learn frequently used patterns in Python programming.

This course is designed to cover the grammar of multi-threading, multi-processing, parallelism, and concurrency based on OS knowledge in preparation for technical interviews. You will learn basic knowledge about how to increase execution efficiency with multiple resources.

This course focuses on teaching high-level grammar so that learners who have learned the basics of Python can apply Python to practical use. By understanding the unique features of Python and learning them quickly, you can become familiar with intermediate-level programming.

This course is designed to cover Python metaprogramming and in-depth grammar based on extensive Python development experience and online and offline teaching experience. Furthermore, we have prepared a curriculum that will be helpful for Python job seekers' interviews and technical interviews for experienced professionals. In addition, we will explain the process of directly distributing the library you created to PyPI (Python Package Index).

Learn Figma, the most widely used collaboration tool in the world! Learn the basics of Figma, a design tool for UI design sketching, prototyping, and collaboration, and how to use it in practice.

You can meet Excel as a data analysis tool that can add value to your work. This is a basic Excel course that teaches concepts in a broad and thorough manner from the basics.

This is a class that teaches intermediate and advanced level data analysis and visualization chart creation methods to those who can handle Excel basics. With this class, you can master Excel completely!

This is an introductory web development course for those who are starting programming for the first time. You will learn HTML, CSS, and Javascript and create an Instagram posting card to learn the basic content that is essential for creating a web page.

Java basic concepts, learn them all at once in this lecture. Also, learn them through practical examples such as academic management program, daycare meal management, etc.😀

In this lecture, we will look at service planning and design methodologies for planning services in the IT/tech field, as well as various soft skills that service planners must have. Finally, we will analyze the service using the example of an AI voice recognition service, a UX service introductory lecture for beginners.

From the basics of the Spring Framework to practical usage! Become a developer who can be deployed and actively engaged in the field right away through thorough and comprehensive explanations and examples.

It explains the basic concepts step by step and helps you gain practical knowledge by practicing creating various applications that actually run in a web environment. If you complete this course, you will be ready to work as a programmer.

This is a basic UI design course for those who want to become a new UI/UX designer or learn about UI design. You will learn basic knowledge about UI design and design tips that are essential in practice.

Learn about the concept of UX (User Experience) and explore today's UX design processes and design trends, and learn about the concept of UX/UI in general.

This is a live video of Jung Heung-soo from Heung Button, which was broadcasted on January 23 as part of the <2025 Know Yourself Know Your Enemy Relay Live Campaign>.

The fact that you can analyze data more easily and effectively with Python Pandas instead of Excel! Learn the basic functions of the Pandas library and how to use it in practice through financial data analysis.

The renewed version of 생활코딩's first web development lecture, <WEB 1 - HTML & Internet>, is exclusively available on Inflearn!

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.

This is a course covering the GitHub notebooks and bonus content from <Build a Large Language Model from Scratch> (Gilbut, 2025). GitHub: https://github.com/rickiepark/llm-from-scratch/ <Build a Large Language Model from Scratch> is the Korean translation of the bestseller <Build a Large Language Model (from Scratch)> (Manning, 2024) by Sebastian Raschka. This book provides a way to learn and utilize the operating principles of large language models by building a complete model starting from scratch with OpenAI's GPT-2 model.

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 :)

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.

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

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.

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.

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

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!

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.

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.

You use ChatGPT, but haven't you found it difficult to explain why you get certain answers? "RAG, agents, fine-tuning... I know the terms but find it hard to explain them precisely" "I'm at a loss for words when I hear LLM-related terminology" "Explaining concepts in AI meetings is always vague" This course was created specifically for people like you. This course is a theoretical lecture designed to understand LLMs as a 'structure' rather than a 'tool'. It's not about how to use ChatGPT or Gemini, but about building a framework that allows you to explain why they work the way they do.

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.

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

"Your first step to creating a customized LLM with LoRA-based lightweight fine-tuning!" This is an introductory hands-on course designed so that even those new to LLMs can easily follow along. We minimize complex theory and guide you step-by-step through the entire process: loading the model → applying data → training → comparing results. In a short time, you'll directly experience the workflow of cutting-edge lightweight fine-tuning techniques like LoRA and QLoRA, and gain an intuitive understanding of "how LLM fine-tuning works." Even without extensive resources, experience the satisfaction of creating an LLM specialized for your domain!

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!

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.

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