Business Information Visualization Skills Practical Tableau Quick Start!

You will learn how to develop data/machine learning web applications through 5 practical projects. You can easily and quickly build and deploy web applications with Python and Streamlit. (Updated in June 2025)

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

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I'll explore ADsP certification passing strategies and learn summarized memorization subjects. Reference book: "Everyone's ADsP Cheat Sheet" https://wikidocs.net/book/18829

What does the 'Business Information Visualization Competency Certificate' course teach? This certificate course focuses on developing the ability to analyze data well, visualize it in an easy-to-understand way, and clearly and effectively convey necessary information when making important decisions in a company or organization. In simple terms, it's a course that teaches not just how to view data, but how to find the hidden meaning within it, and how to express it using images, tables, and graphs so that it can be clearly explained to others. Through this course, you will: Develop the ability to think strategically through data, cultivate practical skills immediately applicable to real work, and enhance your expertise and competitiveness. Through this lecture, develop the ability to connect management and data, and take another step forward as an expert in understanding and explaining data.

This lecture aims to systematically learn the essential core concepts and functions absolutely necessary for the Business Information Visualization Practical Exam (Tableau), based on the exam guidelines of the organizing institution. It is structured around practical exercises so that you can freely use the functions frequently tested in the actual exam, and through solving mock exam problems of types A and B, you can improve your understanding of the exam types and your problem-solving skills together. Lecture plan and materials can be checked at https://github.com/hansikyung/Tableau_OneTime.

SQLD, where should I start? This course is for you who feel so overwhelmed; you'll meet a changed you after completing it. SQLD All-in-One Pass!

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

A current professional data analysis instructor at a large company who passed the Big Data Analysis Writer and Practical exams in one go will help you prepare quickly by summarizing the key points.

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.

I'll explore ADsP certification passing strategies and learn summarized memorization subjects. Reference book: "Everyone's ADsP Cheat Sheet" https://wikidocs.net/book/18829

An easy-to-understand introduction to data lecture by Korea's first data humanist, Shin Do-yong! Let's learn data-based thinking to properly read and utilize massive amounts of data!

Through this lecture, students are expected to be able to check actual materials such as big data contests and self-introduction essays and determine the direction of their studies and job preparation.

If you are curious about the various possibilities and future prospects of generative AI, including ChatGPT and Clova X, that can be used for data analysis, come to our seminar this May!

Here are some key competencies that are often overlooked by others in the fiercely competitive and complex semiconductor process job market.

Learn how to map GIS (Geographic Information System) data through our Digital Mapping Workshop. Create your own digital mapping tool, including how to visualize your data on Canvas.

Here’s an example of the synergy that can be created when combining Tableau Desktop and Server/Online. Let’s build a pipeline together to see how data can lead to concrete actions!

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

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.

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!

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.

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.

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.

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.