[7-Day Complete] Pass MS AI-900 Certification in One Go

The era of AI simply providing answers is over. Now is the age of LLM Agents that make decisions and take actions on their own. This course is an introductory lecture where you learn the core principles and structure of agents by implementing them yourself in just 90 minutes of hands-on practice. With minimal complex theory and a code-focused practical flow, you can directly experience "how AI makes decisions and uses tools." Beyond prompt engineering, let's take the first step into AI automation together.

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.

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.

You can implement hands-on practice of infinitely generating cryptocurrency trading signals automatically using ChatGPT and Python, and backtesting and validating them. Additionally, you can learn how to combine all the strategies automatically generated by AI into a single strategy and apply it to actual trading.

Introducing AI entry-level study methods for undergraduates.

AI writes on my Slack and Notion for me? Work smarter with MCP that surpasses the limitations of existing AI!

The Latest Trend in Generative AI, AI Agents! How to Stay Ahead with Cursor, which handles all development tasks, and MCP, which expands functionality!

This is a lecture that studies Vision Transformer, one of the latest deep learning technologies, and implements a paper using Pytorch. Come experience the new future of the vision field with me!

You can learn everything from basic usage of generative AI to automation and creating customized AI chatbots for practical work applications all in one comprehensive course.

# Silicon Valley Internship That Won't Get Cut Even in the AI Era & Complete Course on 30 Big Tech System Designs & Open Source Practical Contributions All students who submit course missions can apply for an AI startup internship in Palo Alto, USA, with exemption from document screening and guaranteed interview opportunities. This course involves designing and scaling 30 real-world system designs based on big tech cases including Netflix, Tesla, Meta, and Tinder. Finally, you'll design your own service from architecture → DB → scaling, contribute to an actively operating open source AI coding agent project (achieving 1.8k downloads per week) to complete your portfolio, and finalize your resume.

Solve the point where 80% get stuck at makeathons. Complete Raspberry Pi · Computer Vision · LLM · 3D Design in 4 weeks! Achieve top rankings at makeathons with a demonstrable smart mirror PoC!

“The era of merely asking AI and getting answers is over.” Now, AI acts on its own. 'Action-oriented AI agents' have emerged that read emails, check remaining annual leave in HR systems, schedule meetings, search internal documents to summarize information, and organize necessary images and links. What's surprising is that all of this can be created even if you're not a developer. By leveraging the Azure AI Agent platform and Microsoft's latest frameworks (Semantic Kernel, AutoGen, etc.), anyone can now build multi-agent systems deployable in actual work, without coding. Directly create 'working AI,' 'connected AI,' and 'AI that judges and moves on its own.' The future is no longer a distant story. It begins now, at your fingertips.

This course will help you become a deep learning-based computer vision expert needed in the field through in-depth theoretical explanations of Object Detection and Segmentation, along with practical examples that can be immediately applied in real-world work environments.

This lecture is for those who have no knowledge of artificial intelligence, machine learning, deep learning, or data analysis but would like to experience it. I will explain the entire process.

Learn how to use OpenCV and process images through a practical implementation of business card recognition. OpenCV is briefly explained, and the OpenCV functions required to implement business card recognition are explained in more detail. In other words, rather than a basic course, it provides an essence for the practical application of business card recognition. It also includes a method of utilizing Tesseract and Microsoft's OCR engine. The source code of this lecture is based on Python, but since you will learn the OpenCV classes and functions used and the image recognition and processing technology, it will not be difficult to apply it to Android and iOS based on this. Those who take the course will be provided with lecture slides and actual business card recognition source code. The lecture contents were further improved and verified through three offline seminars in January and February 2017, and the instructor has carefully recorded them again for online use. These are the OpenCV functions used in this lecture. cv2.Canny() cv2.GaussianBlur() cv2.VideoCapture() cv2.adaptiveThreshold() cv2.approxPolyDP() cv2.arcLength() cv2.boundingRect() cv2.boxPoints() cv2.contourArea() cv2.convertScaleAbs() cv2.createTrackbar() cv2.cvtColor() cv2.destroyAllWindows() cv2.dilate() cv2.drawContour s() cv2.findContours() cv2.getAffineTransform() cv2.getPerspectiveTransform() cv2.getTrackbarPos() cv2.imread() cv2.imshow() cv2.imwrite() cv2.minAreaRect() cv2.namedWindow() cv2.rectangle() cv2.resize() cv2.threshold() cv2.waitKey() cv2.warpAffine() cv2.warpPerspective()

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 create a deep learning analysis environment in the cloud using Docker. When Docker images managed by Google, MS, etc. are combined with the cloud, you can work with the latest deep learning analysis methods on your computer.

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

Automate Creating YouTube Shorts with AI!! Learn from scratch how to automatically create YouTube Shorts with n8n. Build a complete workflow that runs from text→image/music→video creation→upload all at once. Practice distinguishing between test mode/production mode and tips for saving costs. Complete 3 ready-to-use automation templates by the end of the course. Learn step-by-step from node placement so you can follow along even without coding knowledge. Let's automate AI YouTube Shorts production together!

If you want to create your own AI service without coding, this course is the perfect solution. Using the Dify no-code platform, you can create high-quality AI apps with just your ideas. Instead of complex theory, it's structured around hands-on projects, allowing both AI beginners and working professionals to develop practical skills.