[Renewed] Beginner’s Python Machine Learning Bootcamp (Easy! Learn by Solving Real Kaggle Problems) [Data Analysis/Science Part 2]

This course teaches the fundamental skills needed to learn the entire Python data analysis process for beginners in data analysis. As an e-commerce planner and developer who actively uses data analysis techniques in the field, I designed it to help you easily learn the full Python data analysis process and apply it right away.

This is Part 1 of a roadmap course that neatly organizes, in a short amount of time, the essential computer science (CS) knowledge you need to excel at development and data. This course has also been used for years as an in-house course at top companies in Korea. Based on 20 years of experience in the field, ranging from systems software to web and app development and data science, this course systematically and thoroughly covers the core concepts you need to excel at development and data—while keeping them easy to understand.

Master intermediate-to-advanced SQL and build solid SQL data analysis skills by solving 101 real-world data analysis problems together.

This course is Part 3 of the Full-Stack course series, designed to help you thoroughly master the latest server technologies and Docker. To enable you to genuinely incorporate Docker into your tech stack, the course meticulously tests Docker’s various options, covers related technologies such as Linux that you need to understand for Docker, and is structured so that you can even build complex real-world services.

A full-stack series course aimed at beginners, based on real-world experience developing actual web services, with the goal of building web and app services to a level suitable for actual commercialization. As Part 2 of this series, this course thoroughly covers the latest HTML5, CSS3, and Vanilla JavaScript (Javascript) + ES6, including responsiveness and compatibility, among the many available frontend technologies.

This is a full-stack series aimed at beginners, with the goal of developing web and app services to a level that can be genuinely commercialized, based on real-world experience developing actual web services. As the first step (part1-1), this course provides an in-depth explanation of intermediate Python for full-scale development, backend implementation with Flask [플라스크], and essential web technologies such as HTTP, REST API, and the MVC pattern.

Learn NoSQL technology for handling big data, one of the fundamental technologies used in the full-stack and data science fields at modern startups. MongoDB is one of the easiest NoSQL technologies to learn and use quickly. In this course, you will learn the basics of MongoDB in a short time, as well as how to work with and utilize MongoDB using Python.

This course has been newly designed to help you gradually learn the mathematics and theory needed to understand deep learning, PyTorch-based implementation, transfer learning, and the core GPT Transformer, based on the instructor’s experience of struggling when first learning deep learning.

Through this course, you will learn about SQL and databases, SQL syntax, database design for practical use, how to use databases through programming, and real-world applications of data analysis.

For those who want to learn data science, big data, and web scraping, (1) we summarize the most essential Python syntax in a short time, and (2) help you become familiar with Python and web scraping through practical scraping programming.

A FastAPI course for modern full-stack and backend development that is easy to use and delivers high performance. It covers backend concepts step by step, the core syntax of FastAPI, and asynchronous database usage, all organized clearly through well-structured materials and projects.

This course covers everything from the basics of Dart programming to Flutter’s fundamental and intermediate features, and even integrating the backend Firebase to build a real-world project! It is a comprehensive course that lets you learn Flutter step by step.

This course teaches the fundamental skills needed to learn the entire Python data analysis process for beginners in data analysis. As an e-commerce planner and developer who actively uses data analysis techniques in the field, I designed it to help you easily learn the full Python data analysis process and apply it right away.

🧩 Rather than focusing on complex formulas or theory-centric explanations, the goal is to learn the core concepts of recommendation systems by directly implementing programs. 🛠️ Through a total of 12 diverse and practical examples, we have progressively designed recommendation systems that can be utilized in real-world environments, including content-based recommendation, collaborative filtering, and deep learning recommendation.

This is a lecture on implementing various artificial neural networks using PyTorch, a deep learning framework with very high utility in the field of artificial intelligence.

We guide non-majors and beginners to quickly obtain the Big Data Analysis Certification (Practical Exam)! Keep the theory light and the practice solid—focusing on core points that are guaranteed to appear on the exam through past questions, without the need for complex background knowledge.

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.

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

This lecture is designed for job seekers preparing for Evaluation and Analysis roles in Samsung Electronics' DS Division (Memory, S.LSI, Foundry, TSP, AVP) and PE, AE, and Solution PE roles at SK hynix, who are struggling with the differences between business units and job functions. You will learn how to categorize job titles by company based on the actual workflow of Product Evaluation roles and how to translate your major-related experiences into professional terminology suitable for resumes and interviews. We will help you establish an application strategy by connecting experiences in Analog circuit design, Verilog/FPGA, process experiments, and data analysis with key industry terms such as Yield, Wafer Map, Shmoo Plot, and Failure Analysis.

Learn NoSQL technology for handling big data, one of the fundamental technologies used in the full-stack and data science fields at modern startups. MongoDB is one of the easiest NoSQL technologies to learn and use quickly. In this course, you will learn the basics of MongoDB in a short time, as well as how to work with and utilize MongoDB using Python.

Starting with the question, "If I were on the Titanic, would I have survived?", this course completes a full-stack project where you develop an AI model to predict survival probabilities based on real data and deploy it as a web service. You will gain hands-on experience in the entire process of AI and web development, from deep learning modeling using PyTorch to building a backend server with FastAPI and implementing a user interface with Next.js.

Through this course, you will learn about SQL and databases, SQL syntax, database design for practical use, how to use databases through programming, and real-world applications of data analysis.

"Throw away the cliché AI theories and chatbot examples scattered all over YouTube. This is Korea's one and only '7 Major Industry Integrated Manufacturing AI Bible' that understands the language of manufacturing and pierces through the essence of the process." Hello, I am Byte Detective, your knowledge sharer. Currently, countless companies and practitioners are calling for 'Manufacturing DX (Digital Transformation)' and 'AI Adoption.' However, the majority of courses on the market are limited to vague theories from IT developers or consultants who have no understanding of the harsh practical realities of the manufacturing field. This course is not a lecture for the sake of theory. By organically combining the actual domain knowledge of Korea's top 7 representative manufacturing industries with the latest AI frameworks, it provides a 'Practical Manufacturing DX Scenario Architecture' that can be applied to the field starting tomorrow.

Through a systematic curriculum of 40 lectures, you will learn everything from the basic theories of AI to the applied AI technologies of each algorithm. Through mathematical intuition and R coding algorithm learning and practice, you will develop immediately applicable AI model development capabilities, covering everything from designing algorithm models for data analysis, machine learning, and their application tools to selecting and utilizing them.

This course is a hands-on program for practicing the fundamentals of machine learning mathematics and statistics using Python. While machine learning and deep learning require programming skills, a mathematical background is necessary to understand the underlying principles. Through this course, you can step-by-step master the foundational mathematics required for artificial intelligence.

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.

🚀 Practical AI Anomaly Detection with Databricks! 💡 Stop using expensive and slow models! From large-scale data optimization to real-time deployment, complete an anomaly detection AI that can be used immediately in corporate practice.

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.

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.

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!

In this class, you will learn techniques for retrieving (crawling) and processing data from various operating sites using Python, and apply them directly to various examples that you may encounter in the field. Through this, you will learn techniques that focus on solving practical problems based on an understanding of the basic principles of how the web works, rather than one-dimensional task automation by copying and pasting given codes, and accordingly, you will be able to collect and process data from any site in the future. You will also learn how to resolve various exceptions that occur in this process with code, and ultimately, you will be able to solve and automate various problems that occur in daily life with programming thinking.

Have you been getting stuck on linear algebra formulas every time you try to study AI? Instead of memorizing formulas, this lecture shows you visually how vectors and matrices actually move in space. By the end of the course, you will be able to interpret the mathematics behind neural networks, PCA, and SVD on your own.