Data mining

Let's acquire the Python coding skills necessary for artificial intelligence by learning the basics of the Python programming language!

Let's understand the main algorithms of machine learning and deep learning, and learn about artificial intelligence!

Let's learn how to translate real-life and major problems into actual computer programs and practice using Python-based artificial intelligence tools!

Let's learn various data structures and algorithms and develop practical skills by implementing them through programming!

Let's build the skills to develop web applications using React and cultivate the capability to apply them in practice!

Let's develop the ability to find rational decision-making models based on mathematical thinking by understanding various elements of AI and data, and solving real-world problems using ChatGPT and no-code programming!

Let's develop specialized skills in programming skills, algorithm skills, and statistical analysis skills!

Let's learn how to collect data from the web and create a supervised learning model for machine learning!

Let's design, implement, and develop while learning the basic concepts of the C++ language and object-oriented concepts!

Let's build a solid foundation in Python and solve data analysis problems!

Let's develop practical data-driven administrative capabilities to empirically solve administrative and policy problems by analyzing public data with R and Python!

Let's understand model algorithms for machine learning and deep learning by utilizing Keras!

Let's analyze and visualize data and learn machine learning concepts using Orange 3!

Let's collect and refine data through public data, web scraping, and more, and perform exploratory data analysis!

Learn how to use Git and GitHub and use them for collaboration!

Understand and learn about Artificial Intelligence and AI ethics, and strengthen your AI digital capabilities by integrating them with your own field of study!

It improves logical thinking skills, develops an understanding of how to use programming tools, and develops the ability to design algorithms for problem solving.

ChatGPT, become a creator using generative AI!

Let's create simple and fun 3D modeling with Tinkercad!

Let's look into how to deploy Abyss for non-majors!

How to Read the World with Data: Explore Your Own Data Science! Dive deep and practically into the tools and techniques that form the core of modern data science. In particular, you will learn how to analyze data and implement algorithms using Anaconda, Numpy, Pandas, and Scikit-learn, essential components of data science.

Stop using difficult formula-based Excel! This course allows you to utilize advanced Excel features with just a few clicks. Effectively learn unfamiliar yet highly practical advanced Excel functions to master task automation, data preprocessing, data modeling, and advanced visualization skills all at once, and take your data analysis level to new heights!

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.

Based on the instructor's own failed experiences when first learning machine learning, this is a newly designed course that differs from existing lectures, making it easy to understand machine learning and apply it to real-world problems

🧩 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 course covers how to leverage AI in the food and pharmaceutical manufacturing industry to enhance productivity and quality. Through real-world case studies, you'll learn how AI is applied in key stages such as raw material management, production processes, quality inspection, and regulatory compliance, while understanding defect rate reduction and efficient operational strategies. Through this course, learners will master ▲characteristics of the food and pharmaceutical industry and the necessity of AI adoption ▲data-driven quality management ▲predictive maintenance and equipment optimization ▲regulatory compliance monitoring and risk management ▲analysis of domestic and international implementation cases, gaining strategies and insights that can be immediately applied in the field.

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.

Let's learn how to collect data from the web and create a supervised learning model for machine learning!

ADsP Summary + Past Exam Solutions. Reflects August 2025 46th Exam! (Continuously Updated!)

Make AI data analysis and modeling results into a Web Program.

Learn how to process big data from a Silicon Valley software engineer & how to develop big data code with Apache Spark using Python. I am a 14-year software developer who handles everything from web applications to big data and SRE & DevOps with Python. Don't miss this opportunity to learn about Apache Spark, which is essential for big data professionals, in an easy and in-depth way using Python!

This is a Python basics course for starters who want to grow as data analysts. - Those who want to do data analysis but don't know Python - Those who want to learn machine learning with Python - Those preparing for the Big Data Analytics Engineer practical exam - Those who want to develop machine learning-based applications with Python

Let's develop specialized skills in programming skills, algorithm skills, and statistical analysis skills!

🚀 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.

SSIS, SSAS, MachineLearning, BI, ETL. You can learn important technologies that cannot be found in domestic books, YouTube, lectures, blogs, and academies. I also recommend it to those who are interested in employment at domestic large companies, American large companies, and American state funding agencies.

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.

Let's use the R language, which processes data easily and conveniently, to develop computer program utilization skills related to one's major, even for non-computer majors!

Learn a systematic approach to S&P 500 pair trading with Python. Lay the foundation for an investment strategy that excludes emotions through professional data analysis.

It improves logical thinking skills, develops an understanding of how to use programming tools, and develops the ability to design algorithms for problem solving.