No more AI courses filled with just theory. A current CEO who won the KT AI Excellence Award will teach you everything from text to video and game creation - 'practical secrets you can learn today and see results tomorrow.' Achieved 16.4 million won in Wadiz funding! The course that hundreds were enthusiastic about. We'll spoon-feed you the 'real practical' generative AI cheat codes that even non-majors can use to create web novels and videos right away. From planning to high-quality video production, learn how to finish with AI in a snap what would take a week if you hired an expert. We reveal the fastest route to creating results without trial and error.

This course is built from real-world experience designing and deploying production-grade LLM applications on Azure. Rather than focusing on toy examples or isolated notebooks, I guide students through the exact challenges they face when moving from experimentation to real systems: data ingestion, vector storage, service orchestration, cloud deployment, and security. Throughout the course, I break down complex Azure services into clear, practical steps, explain why each architectural decision is made, and show how components work together in a scalable system. Students learn by building, debugging, and deploying a complete LangChain-based application, gaining confidence in solving real infrastructure and application-level problems.

"Are you still studying with coding books?" A course, rated 5.0/5.0 by MBA and business undergrads at a London management university. You can take AI data analysis lectures from home. Even for humanities-background non-majors: practical data analysis skills immediately usable in the field, plus a data analysis portfolio for job search completion. I am a British Professor (British Professor) teaching data analysis and project classes with ChatGPT, no coding knowledge required.

This course conducts hands-on practice related to Diffusion models among generative artificial intelligence models. By reading and implementing the prompt-to-prompt paper, which is a representative Diffusion model application paper, we expect to cultivate the ability to understand the latest artificial intelligence papers.

Stop worrying about the dev team - I'll build it myself now! This course helps professionals in planning, marketing, sales, and other practical roles implement core web service features on their own using AI tools, without needing developer assistance.

This is a course to learn about Airflow, an Orchestration tool for efficiently building and managing data pipelines. Welcome to the Airflow Master Class, where even beginners can learn step-by-step!

With the advent of the AI era, building data pipelines has become a core competency that determines a company's competitiveness. Learn how to build efficient data pipelines using Airflow, the most widely used tool, directly from a Silicon Valley expert (formerly Head of the Data Team at Udemy, currently a professor in the Data Masters program at San Jose State University) with practical experience and extensive lecturing experience.

From work productivity to monetization, we'll teach you everything about AI agent development that you can apply directly to real-world tasks. Become an "AI Agent Development Expert" by directly developing 7 agents based on technologies including n8n, CrewAI, LangGraph, Google ADK, multi-agent orchestration, RAG, multimodal, MCP, A2A, and more.

This course is designed to learn the fundamental theories and practical processes necessary for applying AI modeling and service planning to real-world work environments. Learners can acquire essential foundational knowledge to skillfully perform AI modeling projects and experience various practical procedures used in actual business settings. The course is specifically structured to provide step-by-step learning of the entire workflow from AI service environment analysis → goal setting → requirements analysis → service model design → scenario planning → utilization planning → execution plan development → performance evaluation planning. Through this approach, learners can develop systematic thinking and practical application skills for how to introduce and utilize AI from business and service planning perspectives, rather than limiting themselves to purely technical learning. Upon completing this course, learners will understand the overall planning and execution process of AI projects and will be able to strengthen their capabilities as AI service planners, PMs, and data-driven strategists in actual corporate environments.

This comprehensive course teaches you how to build any full-stack application using AI tools like Cursor AI, Claude Code, v0, ChatGPT, and Replit. Learn coding basics, front-end and back-end development, database integration, debugging, and deployment. Perfect for beginners and anyone looking to leverage AI to build real web and mobile apps quickly and efficiently.

Learn why and how to handle data exploration (EDA), data cleaning, scaling, outlier handling, log transformation, and categorical encoding in real-world applications. You will also learn how to merge tabular data and process (unstructured) time series data.

Get a clear overview of exam types and trends at a glance! Sharpen your practical skills with a total of 120 questions. The perfect preparation for the AWS AI Practitioner exam, designed for systematic learning even when studying alone.

Simply by entering a US company ticker, this system automatically collects financial accounting data, competitor analysis, recent news, and stock price information, then performs in-depth analysis using the OpenAI GPT API to generate professional investment reports. The final results are automatically uploaded to Notion. By learning fundamental financial accounting concepts and terminology, even engineers can utilize this for competitor benchmarking, persuading supervisors, and planning new solutions. Build high-performance API servers with Python and FastAPI while learning asynchronous programming, AI integration, and practical fintech skills. Even beginners can easily follow along to complete a system applicable to real investment and business scenarios, helping them grow into developers suited for the AI era.

Develop a deep understanding and intuition for calculus. Solve problems and implement algorithms by hand and in Python.

From the basics of machine learning & deep learning! Creating and utilizing classification/regression/clustering/artificial neural networks with Python

Write meeting minutes, build apps, and even create videos all on one platform. Become an AI multiplayer with Google AI Studio!

There is no need to ignore or fear machine learning. Machine learning is easy, but let's think about where to apply machine learning. The direction of machine learning expansion in Java is expected to be similar to the current Python, R strength, and future coexistence of Python, R, and Java, like iOs. The purpose of this lecture is to build a DIKW collaboration system between domain experts and IT professionals.

Stop using print()! Learn easy and powerful logging with Python's loguru library. From basic concepts to file management, FastAPI web app integration and Slack notifications, we'll teach you step by step with hands-on practice.

Through this course, students will learn various reinforcement learning theories and implement them themselves, as well as create a reinforcement learning environment to test the reinforcement learning algorithm implemented using Unity Machine Learning Agents.

A course chosen by 3,000 students! Updated to GPT-5 version! How far can you go with ChatGPT? Create automated stock trading applications and web investment reports!