Understanding Data Literacy

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 develop the capacity to extract valuable information from big data and support decision-making!

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!

We introduce methods for planners and marketers without data analysis experience or technical skills to try data analysis at the most basic level, complete with various examples. Built on years of hands-on practice with over 2,000 participants in more than 100 companies and public institutions, the content is designed around the most practical analysis methods for data non-experts.

This is a course for PMs who want to utilize data. It covers the entire process of using data in a PM role, capturing the full workflow from your first day at a new job to the beginning and end of a project. It is an introductory data course designed to build your thinking power, covering everything from data-driven and logical thinking to metric definition, log design, experiment design, and building a data culture. Although it was created for PMs, the content is also highly beneficial for data analysts (in fact, many analysts have already taken this course). Additionally, many professionals in marketing, design, and business planning roles are also taking the course.

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.

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

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.

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.

Data Visualization Storytelling That's Perfectly Achievable with Excel Alone

Learn the problem definition and hypothesis formulation process, core competencies for data analysis!

"Have you given up on data analysis after only studying the tools?" PMs at large corporations only need to look at the data already implemented by the analysis team. However, PMs at startups or side projects are different. They must build the 'foundation' themselves—from designing logs and labeling them to collecting the data. "Everyone says data is important, but what exactly should I implement and where in my service?" Stop getting lost in abstract concepts. Checking login history is the true beginning of Data-Driven Decision Making (DDDM).

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.

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

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!

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.

Analyzing customers, markets, and revenue patterns—you no longer need to learn it yourself. Just ask AI, and expert-level analysis and strategies are completed in an instant!

🧩 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.

* 100% Practical Curriculum: Focused on hands-on data handling rather than grammar-based learning * Essential Machine Learning Prep: A complete summary of data preprocessing techniques required before AI training * Data Analysis Tool Mastery: Conquer core functions of Numpy (numerical operations) and Pandas (data manipulation) * Deriving Visualization Insights: Transferring data visualization skills using Matplotlib and Seaborn * Building Statistical Foundations: Learning basic statistics and group analysis techniques to identify data characteristics

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.

Data Analysis that Determines Online MD Performance! Learn essential data analysis and strategy formulation techniques necessary for MDs to maximize sales and profit in the e-commerce market.