This course covers how to use queries to build dashboards in Logpresso. We will discuss how to visualize real-time data, trigger alerts, and dynamically drill down and filter as needed.

This course explains how to perform data engineering, including real-time processing and external integration, which are the strengths of Logpresso. It also covers in depth how to assign reference data in real time, the precedence of logically related events, and CEP (Complex Event Processing) for detecting various actions and performing follow-up tasks based on collection intervals.

This article covers how to use the reservation query feature, which automatically schedules execution in Logpresso. Learn how to learn each query pattern for data processing, such as aggregation query patterns that are mainly performed by scheduling, and how to solve problems.

This course is designed to learn how to collect data through Logpresso and normalize the collected data so that it can be queried. In this course, you will learn how to collect data by setting up a collector, how to parse data mixed in various forms, and how to create a collector by installing an agent on a remote server.

In the era of big data, data science is gaining attention as a solution for scientific business decision-making. Through this course, you will learn about various data analysis methods and utilization methods and be able to apply them to your work.

This course is designed for all learners, from those just starting with data analysis to those looking to apply it in practical work, to systematically learn the entire process of data processing and visualization using R. First, in the basic setup stage, we start with installing the development environment and learn how to create DataFrames and Series, building a solid foundation in the fundamentals needed for R programming. Next, we move on to learning core functions, focusing on hands-on practice with the most frequently used features in data analysis such as indexing, slicing, sorting, filtering, and handling missing values. After building the foundation, we expand to intermediate functions, intensively covering features essential for actual data analysis work such as date and time data processing, groupby operations, data merging (merge, concat), and function application (apply, lambda). Through this, you can develop the ability to handle complex data structures beyond simple data manipulation. Finally, in the visualization section, we cover various visualization techniques including line graphs, histograms, box plots, and time series graphs to learn how to express data more intuitively. Through visualization, you can also acquire the ability to effectively communicate analysis results. In particular, this course is structured not to stop at theoretical learning, but to allow immediate application of learned content through various examples and step-by-step practice. Therefore, students can naturally develop practical skills just by following the course and further secure data analysis capabilities that can be applied to actual projects.

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.

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.

It's now an era where data speaks, not intuition. Learn data analysis easily with ChatGPT!

Understand the core of big data business and provide insights on how to utilize it in marketing strategies in the field.

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

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.

This course is a course that practices the basics of machine learning mathematics and statistics using Python. Machine learning and deep learning require programming skills, but they also require a mathematical background to understand the principles. Through this course, you can gradually learn the basic mathematics required for artificial intelligence.

We guide non-majors and beginners to quickly obtain the Big Data Analytics Engineer practical certification! Theory lightly, practice thoroughly - even without complex background knowledge, we focus on learning only the essential points that appear on the exam, centered around past exam questions.

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

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.

What do you learn in the 'Business Information Visualization Certification' course? This certification course focuses on developing the ability to analyze data well, visualize it in an easy-to-understand way, and clearly and effectively communicate the information needed when making important decisions in a company or organization. Simply put, it's a course where you learn the skills to not just look at data, but to discover the hidden meanings within it and express them through pictures, tables, graphs, etc., so you can explain them well to others. Through this course, you will: Develop the ability to think strategically through data, build practical skills that can be immediately applied to actual work, and enhance your professional expertise and competitiveness. Through this lecture, develop the ability to connect business and data, and take one more step toward becoming an expert who understands and explains data.

Time Series: Become a Data Analysis Expert! Let's be analysts strong in theory & practice!

Repetitive pipeline management in Data Warehouses (DW), now free yourself from that painful cycle with dbt! Building on the efficiency provided by dbt, become a data analytics engineer who creates higher value through business-centric data modeling, effective data lifecycle management, and more.

SQLD, where do I even start? This course is for those who feel completely lost - you'll meet a transformed version of yourself after completing it. SQLD All-in-One Pass!

We explored the essential Python syntax necessary for big data analysis and, through various examples, presented methods such as big data file processing and visualization.

Revolutionize your stock investments with AI! In this lecture, you will directly build a real, working AI automated trading system targeting the top 25 NASDAQ stocks. We provide a special opportunity to gain experience and know-how through simulated investments with the 한국투자증권 API, and to perform AI stock automated trading with a real account. Even stock beginners will have no problem. We will easily explain basic stock concepts and why you should invest in US stocks, and provide all source code and remote support. From now on, investment is essential for the next 60 years of our lives. Create your own AI investment partner that will be with you!

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.

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!