The current state of AI development as felt through meeting 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.

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.

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.

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).

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.

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 is an introductory web development course for those starting programming for the first time. By learning HTML, CSS, and JavaScript and creating an Instagram post card, you will learn the essential basics required for web page production.

Do you want to create a tool that can help you with your real-world investments using Python? In this course, you will learn how to create an interactive web dashboard for financial data analysis for intermediate Python users and learn about pair trading strategies for in-depth quantitative work. We hope that you will be able to create your own useful analysis tools to help you analyze financial data more powerfully and make wise investment decisions.

Leverage Python to create your own indicators and a convenient tool for securities analysis!

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>.

It explains the basic concepts step-by-step and helps you build practical knowledge by creating various applications that run in real-world web environments. By completing this course, you will be ready to be deployed immediately as a professional programmer.

You can watch the opening and presentation sessions of Infecon 2024, a festival for growing IT professionals, again in video.

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!

The renewal version of Life Coding's first web development course, <WEB 1 - HTML & Internet>, is being released exclusively on Inflearn!

This is a lecture that captures the scene of a product design meetup held by former Toss Product Designer Kang Young-hwa and Inflearn! You can learn many insights and work know-how from a 10-year product designer!

This is a video of the meetup that took place at 7pm on January 31st.

This is a recorded video of the TDD online live meetup held in July 2025.

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 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 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.

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

This course covers the entire process of evolving ChatGPT from a simple conversational AI into an intelligent AI Agent that performs real-world tasks. By utilizing the three core frameworks—LangChain, LangGraph, and LangSmith—you will build AI Agents that can be used immediately in practice.

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.

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.

It explains the fundamental principles of large language models like ChatGPT, focusing on theory.

What if AI could directly open a browser and write shell scripts to resolve server issues? Through practical automation know-how implemented with OpenClaw across Windows and Linux, we guide you on the shortest path to completing your own powerful remote development environment without complex configurations.

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 designed for those who use AI but are confused about how much they can trust it. It covers how to use AI in your work or creative process without overdoing it, ensuring it provides actual value. Rather than requiring professional development knowledge or complex tools, it focuses on how anyone can effectively integrate AI into their own workflow. Instead of teaching complex prompt engineering, the course focuses on the mindset of **knowing when to use AI and when it's better not to**, as well as **how to verify and refine AI outputs** rather than trusting them blindly. Through this course, you will establish criteria for using AI not as an automation tool that replaces everything, but as a **practical partner** that helps organize your thoughts and assists in your work.

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.

In the era of AI, developers must become "integrators" rather than mere coders. This course covers how to combine Unreal Engine with the latest AI tools like ChatGPT and Claude into the actual C++ development process. Through practical examples designed by Unreal Authorized 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.

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.

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

You use ChatGPT, but haven't you found it difficult to explain why it gives certain answers? "I know terms like RAG, Agents, and Fine-tuning... but it's hard to explain them accurately." "I get tongue-tied whenever I hear LLM-related terminology." "Conceptual explanations are always vague during AI meetings." This course was created specifically for people like you. This is a theoretical course designed to help you understand LLMs not just as a 'tool,' but as a 'structure.' It doesn't teach you how to use ChatGPT or Gemini; instead, it establishes the foundation so you can explain exactly why they work the way they do.

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 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.

LLM and Agent, the fundamental technologies behind AI like ChatGPT. LLM is currently the technology that has come closest to AGI. In this lecture, we will explore LLM and Agent technologies from a layperson's perspective.

An introductory AI lecture tailored for those new to artificial intelligence! It easily summarizes core concepts from data to generative AI. The goal is not to build AI, but to achieve a level of practical understanding where you can ask the right questions and explain the technology.