[2026 New] Advanced Data Analytics Semi-Professional (ADsP) Certification

The Big Data Analysis Certification is a national certification exam held twice a year. For those preparing for the exam, I have provided detailed lectures covering everything from the basics to core concepts. The difficulty of the exam increases with each session. To address this, I have provided various essential contents starting from the fundamentals to help improve the passing rate.

The Big Data Analysis Certification is a nationally recognized certification exam held twice a year. For those preparing for the practical exam, we have provided detailed lectures covering everything from the basics to core concepts. As the exam difficulty increases with each session, we have included various essential contents starting from the fundamentals to help improve your chances of passing.

This is a practice exam and latest past exam restoration problem-solving course for those who wish to obtain the Advanced Data Analytics Semi-Professional (ADsP) national certification.

We have included only the essential content so that even non-majors can learn Python easily and enjoyably. We will proceed with detailed lectures and challenge exercises so that beginners can properly learn the ‘essential content.’

This course aims to obtain the state-certified SQLD (SQL Developer) certification. An SQLD refers to a developer who can write accurate SQL to manipulate and extract data while developing application software based on knowledge of databases and data modeling.

If you have learned the Python language, this course will help you improve your Python skills and obtain a certificate through solving Cos Pro Level 2 problems, which will allow you to acquire simple problem-solving skills, analyze output values for input, and analyze requirements.

This course is for those preparing for the CosPro Level 1 exam, covering the COS Pro Level 1 sample problems released by the exam organizer, YBM Net Co., Ltd.

The Big Data Analysis Certification is a nationally recognized certification exam held twice a year. For those preparing for the practical exam, we have provided detailed lectures covering everything from the basics to core concepts. As the exam difficulty increases with each session, we have included various essential contents starting from the fundamentals to help improve your chances of passing.

The Big Data Analysis Certification is a national certification exam held twice a year. For those preparing for the exam, I have provided detailed lectures covering everything from the basics to core concepts. The difficulty of the exam increases with each session. To address this, I have provided various essential contents starting from the fundamentals to help improve the passing rate.

We will help those preparing for the Big Data Analysis Engineer Practical Exam with R to prepare for the exam. We will select and inform you of only the essential parts based on the questions that were on the Big Data Analysis Engineer Practical Exam. If you complete the course, you will be one step closer to passing the Big Data Analysis Engineer Practical Exam. We have reviewed the recent exam questions and uploaded related scripts and data. Also check out the latest exam information.

This course is designed for those who wish to obtain the nationally certified Advanced Data Analytics Semi-Professional (ADSP) certification. As the need for practical data analysis experts in both public and private sectors grows, this course is structured to help participants objectively verify their data analysis skills—essential for data utilization across society—and successfully apply for and obtain the certification.

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

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

Contains the growth history and know-how of portal company N, which achieved rapid growth through cloud services.

Revolutionize your stock investing with AI! In this course, you will directly build a functional AI automated trading system targeting the top 25 Nasdaq stocks. We provide a special opportunity to gain experience and know-how through mock trading using the Korea Investment & Securities API, and then transition to AI automated trading with a real account. Even stock market beginners will have no problem. We explain basic stock concepts and the reasons why you should invest in US stocks in an easy-to-understand way, while providing all source codes and even remote support. From now on, investing is essential for the next 60 years of our lives. Create your own AI investment partner to join you on this journey!

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 should I start? For those of you feeling completely overwhelmed, this is the lecture for you. You will meet a transformed version of yourself after completing the course. SQLD All-in-One Pass!

This is an advanced course where you will directly implement and interpret practical statistical techniques such as sampling distributions, hypothesis testing, regression analysis, and logistic regression using R. By utilizing AI tutors like ChatGPT and Gemini, you will learn everything from code generation to interpreting analysis results and writing reports, allowing you to take your data analysis capabilities to the next level.

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

Through this course, students can improve their Go reading skills and apply them when playing actual Go games.

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.

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

We explain 32 data visualization techniques very quickly and easily from a non-expert's perspective!

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 help even non-computer science majors develop their skills in utilizing computer programs related to their own fields!

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.