[Big Data Learning Center] (Free) Analysis Skill-Up Starting with KNIME

The 65th Open House is about showing how data analysis is enriched by changing the type of variables. It mainly covers scoring, binning, and optimal scaling. The 66th Open House is about learning in detail about the concept and understanding of marginal effects and subgroup analysis.

The 63rd Open House explains the concept of effect size and SPSS's effect size output. It also covers the concept of sample size and power and SPSS's power analysis method. The 64th Open House learns in detail about the extension and evolution of linear regression.

Learn about PSM using KoreaPlus SPSS.

Learn about Text Analytics using KoreaPlus SPSS.

This is a free lecture designed to help those who are new to TEXTOM easily acquire text mining and big data analysis skills through hands-on exercises with examples, rather than focusing on fundamental theoretical explanations.

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.

Let's understand and try policy evaluation with R and R Studio!

The chemical and fine chemical manufacturing industry is a sector that requires complex processes and high safety standards. This course covers strategies for leveraging AI to increase productivity, reduce costs, and enhance safety. You can systematically learn practical skills centered on AI application cases that can be immediately applied in actual field settings, including process data analysis, quality prediction, equipment predictive maintenance, and environmental regulation compliance.

"Big Data + AI Full Stack Development" - The process of building big data that breathes life into AI is carried out in the form of a pilot project. We identify requirements, configure the platform step by step, and perform smart car data exploration and analysis.

SQLD Yellow Book 176 Problem-Solving Course for those who studied but can't solve problems. After completion, you'll go beyond passing to become an expert. SQLD All-in-One Pass!

This course is designed for those aiming to obtain the Data Architecture Semi-Professional (DAsP) certification. It provides a simple and systematic overview of essential exam topics, ranging from basic data architecture concepts to data modeling, data quality, and governance. The curriculum is structured to minimize complex theories and focus on frequently tested concepts, making it accessible for non-majors and beginners to learn without pressure. Build your fundamental skills in understanding data structurally while preparing for the DAsP certification.

"Smart Factory—it sounds cool, but can't quite picture it in your head?" The news talks about the 4th Industrial Revolution and AI factories every day, but when you actually look for information, it's full of "alien languages" like PLC, MES, ERP, and Edge Computing. What non-majors need isn't a complex circuit diagram, but a 'map' that shows how the whole system works. This course strips away difficult engineering jargon and explains everything about smart factories through intuitive illustrations and analogies that anyone can understand.

This is a special lecture that can lay the theoretical foundation to simultaneously prepare for the Microsoft AZ-900 certification, and as the latest content reflecting the scope of questions as of May 2025, by providing content related to core data concepts, Azure's relational data, Azure's non-relational data, and Azure's analytical workloads in a form combining theory and practice, it can be utilized as a meaningful educational opportunity to not only obtain the certification but also take the first step towards becoming a data professional.

We are now in an era where data speaks louder than intuition. Learn data analysis easily with ChatGPT!

Finally, the Probability and Statistics course for everyone is here! Learn the principles of probability and statistics step by step through theory and coding practice. Reference book "Probability and Statistics for Everyone" https://wikidocs.net/book/18165

Data analyst job prep: Lost on where to begin? Get hints at this September seminar!

Did you know that there are different types of data analysts? If you want to know everything about in-house data analysts and consulting data analysts, come to this seminar!

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.

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!

Students who want to learn Hadoop and Big Data will celebrate the amazing advancements in experiencing the world of Big Data through this course!

It covers basic data concepts, useful R functions and packages, and data analysis exercises, to allow anyone to perform big data analysis using R programming.

This course covers practical strategies for leveraging AI in the machinery and metal processing industry to enhance productivity and quality. It analyzes key process data from CNC, welding, cutting, and other operations, explaining how AI technology is applied to reduce defect rates, enable predictive maintenance, and manage worker safety through real-world case studies. Learners will understand AI-based processing optimization methods that can be immediately implemented in the field, from small and medium enterprises to large corporations, and gain insights to realize manufacturing innovation in global competition.

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.

Do you want to get a job as a data analyst? Based on my experience, let's take a look at the tasks for each data role in real companies.