Deep Learning and PyTorch Bootcamp for Beginners (Easy! From Basics to ChatGPT Core Transformer) [Data Analysis/Science Part3]

This course, Part3 of the Full-stack Course Series, solidly teaches the latest server and Docker technologies. It's structured to practically integrate Docker into your tech stack, meticulously testing its options, learning necessary related tech like Linux, and building complex services.

This course aims to teach data analysis beginners fundamental skills for the entire Python data analysis workflow. As an e-commerce planner and developer leveraging real-world data analysis, I crafted this for easy acquisition and immediate application of the full Python data analysis process.

Unlike existing lectures, this course has been newly designed based on the instructor's initial failures in learning machine learning, enabling easy understanding and application to real-world problems.

For those looking to learn Data Science, Big Data, and Crawling, (1) we will summarize the most essential Python core syntax in a short time, and (2) you will become familiar with Python and crawling through practical crawling programming.

This course offers an easy and fast way to learn FastAPI, the latest full-stack and backend framework, along with cleanly organized materials and projects that cover backend concepts, core FastAPI syntax, and asynchronous database utilization in an easy, step-by-step manner.

Learn NoSQL technology, which can handle Big Data, one of the fundamental technologies in full-stack and data science utilized by modern startups. MongoDB is the easiest and quickest technology to utilize among NoSQL databases. In this lecture, you will learn the basics of MongoDB in a short time, and also acquire the skills to manipulate and utilize MongoDB with Python.

Master advanced SQL, solve 101 practical data analysis problems at a professional level together, and build a solid SQL data analysis skillset.

This is a full-stack lecture series based on real-world web service development experience, aiming to help beginners develop web and app services to a level suitable for actual commercialization. As Part 2 of this series, this lecture thoroughly and solidly covers the latest HTML5, CSS3, vanilla Javascript + ES6, considering responsiveness and compatibility within the diverse landscape of frontend technologies.

Based on real-world web service development experience, this full-stack series targets beginners, aiming to develop web and app services capable of actual commercialization. As the initial step (part1-1), this lecture details intermediate Python for full-scale development, backend implementation with flask, and essential web technologies (e.g., HTTP, RestAPI, MVC patterns).

Through this lecture, you can learn about understanding SQL and databases, SQL syntax, database design for practical application, database utilization through programming, and even data analysis application cases.

This is Part 1 of a roadmap lecture that concisely organizes the essential computer science (CS knowledge) needed to excel in development and data, in a short period. This lecture has also been used as an in-house lecture at top domestic companies for several years. Based on 20 years of experience in actual practice, from system SW to web, app development, and data science, this lecture systematically yet easily organizes the essential core knowledge needed to excel in development and data.

This comprehensive course allows step-by-step Flutter learning, from Dart programming basics to Flutter's basic/intermediate features, and integrating backend Firebase for real projects.

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.

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!

This course is a step-by-step learning process that covers the principles of image and object recognition using deep learning, from fundamentals to the latest models. - Building Foundations: Understanding tensors and basic neural network structures with PyTorch - Understanding Images: Learning computer vision concepts, image data structures, and augmentation techniques - CNN Model Training: Hands-on image classification practice with Convolutional Neural Networks (CNN) using datasets like CIFAR-10 - Transfer Learning: Leveraging pre-trained models to achieve fast learning with limited data - Object Detection: Understanding and practicing with the latest object detection models including R-CNN, YOLO, SSD, DETR - Segmentation: Experiencing pixel-level object segmentation through U-Net and Mask R-CNN

Are you interested in AI but tired of always hearing the same lectures? This is a hands-on project that will teach you how to generate and estimate 3D poses from human images and videos, run real code, and build your own data from images.

Unlike existing lectures, this course has been newly designed based on the instructor's initial failures in learning machine learning, enabling easy understanding and application to real-world problems.

This course is a fun project that learns theories and processes images and videos with OpenCV (Open Source Computer Vision Library) and uses deep learning modules (dnn, Deep Neural Network) to identify and recognize faces, eyes, and various objects.

This is a lecture to build an AI portfolio by doing a clone project of airbnb data science team's Amenity Detection project, an excellent TensorFlow utilization case, and organizing the experience on a GitHub blog.

The electronics and semiconductor industry is a field where data-driven management and innovation are particularly crucial due to ultra-precision processes and complex supply chains. This course covers practical strategies that can be directly applied in electronics and semiconductor manufacturing, including defect detection, process optimization, predictive maintenance, and supply chain management using AI technology. Along with real-world cases from global companies, the course also presents low-cost, high-efficiency AI implementation methods that small and medium-sized enterprises can realistically utilize. Through this, students will be able to understand and apply AI-based manufacturing strategies that not only improve productivity and reduce costs, but also build future competitiveness.

This is an introductory course to understand the concepts and application methods of Vision-Language Models (VLM), and to practically run the LLaVA model in an Ollama-based environment, practicing the process of integrating it with MCP (Model Context Protocol). This course covers the principles of multimodal models, Quantization, service, and integrated demo development, providing a balanced mix of theory and practice.

Understand the basic concepts and latest trends of big data, and through technical understanding of big data analysis techniques, extract data patterns to present methods for business application. Through big data, you can create new businesses and develop insights into future business environments.

Essential certification for the AI era, MS AI-900! 🚀 Did you know? ChatGPT operates exclusively on Microsoft Azure! If you want to properly utilize Microsoft Azure OpenAI, which exclusively provides the latest GPT models, now is the perfect opportunity. Grow into an Azure AI services expert through the AI-900 course and master enterprise-grade AI solutions that companies trust. Secure global official certification and enhance your competitiveness as a true AI professional!

AI Artificial Intelligence, it goes without saying that mobile is the trend. But how do you learn machine learning and deep learning and use them on mobile? Now, let's learn useful mobile Computer Vision projects that are used in daily life.

This is a comprehensive machine learning project course that learns various useful machine learning regression and classification projects along with theory using Python and TensorFlow 2 based on Boston Marathon big data.

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

This course is an introductory program designed so that learners who are new to AI technology can easily understand and follow along. Through the lectures, you will learn the basic concepts and usage methods of AI platforms, and conduct hands-on practice directly generating images using various AI tools. Upon completing this course, you will become much closer to AI and acquire the capability to create AI images that can visually implement creative ideas.

This course covers everything from the basics to hands-on practice of AI platforms, and is a program where you can learn AI image generation technology. Learners can understand the fundamental concepts of AI and develop the ability to generate AI images using various tools and technologies. Through this course, you can enhance your understanding of the AI field and learn how to directly generate AI images in real-world applications.

AI is not just a simple technology, but was born from people's questions and the flow of the times. Understanding this flow allows you to connect with any new technology without fear. 👉 "The moment you learn AI's roots through stories, you'll see the context." Start now!

ChatGPT and generative AI have deeply penetrated into our work and daily lives. From deepfakes, hacking, copyright infringement, Naver Whale Bot, to ethics in digital workplaces... The changes AI brings are not just technological issues. Right now, at this very moment, ethical issues are already occurring within the AI you're using. This course focuses on learning about the ethical issues that have exploded with the emergence of generative AI through real-world case studies.

The automotive and parts manufacturing industry is a field where innovation is essential amid fierce global competition and complex supply chains. This course focuses on how AI technology can be applied in the field, explaining actual cases including production efficiency improvement, quality inspection automation, equipment predictive maintenance, and supply chain optimization. From the foundational understanding needed for AI implementation to strategies and risk management considerations for field application, this course covers topics step by step, providing knowledge and insights that practitioners and managers can immediately utilize.

AI is not a technology that suddenly appeared. To properly see AI's present and future, you must understand 70 years of challenges and failures. 👉 "The moment you understand AI history, you can see both its principles and future together." Start right now!