ISTQB AI Testing - Learn Best Practices and Prepare for the Exam

We will develop a banking application using Spring Boot. This course will help you learn how to build an application by testing various problems that arise during development using JUnit.

By developing a simple ReactNative app using the TDD methodology, you will learn the concepts of TDD and practice applying them to ReactNative mobile app development.

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.

We provide CodeTree past questions, as well as algorithms and tips for solving them. We use C++, but since we don't use libraries, those who use other languages can also take the course. (Python code provided)

Navigate the data ocean, explore AI's future. This course explores the vast tech currents of Big Data and AI, examining their innovation in our lives and work.

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

This course is for anyone who is curious about developing test automation on Android and iOS devices. This course will enable you to perform automated testing on mobile devices.

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.

Are you hesitant about writing test code? Experience the A to Z of Spring environment testing through this lecture!

In this course, you will learn about the general types of front-end testing and how to write reliable tests by selecting the appropriate test for the situation.

Through this lecture, you will learn how to identify the overall types of front-end tests and how to write reliable tests by selecting the appropriate test for the situation.

A must-take testing course if you want to become a competent frontend developer. Master testing from beginner to advanced all in one go 👊

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.

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 :)

Software quality is a habit! This course will teach you how to become the best programmer that companies want.

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

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

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.