Advanced Data Analytics Semi-Professional (ADsP) Subject Summaries & Practice Questions

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 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.

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.

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.

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.

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.’

At a time when cultivating data analysis experts is essential, this course is designed to help participants obtain the state-certified 'Advanced Data Analytics Semi-Professional' (ADsP) certification.

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.

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.

This course was created for those who are preparing for the Big Data Analyst practical exam. It will help you pass the exam by learning as concisely as possible, and it will also provide an opportunity for those who are considering their career path to lightly learn about coding and machine learning.

The most definitive way to build the backbone of your data No more fragmented knowledge. From DAsP (Data Architecture Semi-Professional) certification to practical modeling skills, this is the single most perfectly structured masterclass. "Are you still relying on piecemeal memorization for data modeling?" The ability of an 'architect' to translate complex business requirements into clear data structures is the most irreplaceable weapon in the IT ecosystem. This course goes beyond simply passing a certification; it provides practical insights to see through the enterprise-wide data flow.

The only lecture that delves deeply into a specialized field! A subject-specific industry expert will show you the fastest way to pass the exam through a thorough analysis of the exam trends!

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!

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!

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.

This is a practical project lecture that collects data and analyzes big data using Arduino and wind sensors.

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!

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

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 improves logical thinking skills, fosters the ability to understand how to use programming tools, and develops the capacity to design algorithms for problem-solving.

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.

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.

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

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

"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.

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.