[Nuclear House] 2025 Big Data Analysis Article (Written)_Subject 1~2

The trend is big data analysis engineers!
We'll help you pass quickly 🙌

Specialized lectures by field experts to help you pass the exam!

We all just imagined it
Big Data Analyst (Written) Best faculty!
A data analysis expert from/affiliated with a leading domestic company
We've gathered here to help you pass your exam.

Big Data Analysis Engineer Written Test!

A big data analyst is a qualification that certifies that you are an expert in data analysis.
It is one of the most necessary qualifications in the changing future world, and it is necessary to directly handle and analyze data in the field.
It is no exaggeration to say that this is the first step towards becoming a data expert.

Lecture Topic

• Subject 1 Big Data Analysis Planning
• 2nd subject Big Data Exploration

7 questions and 7 answers to help you understand the exam criteria ✨

What are the characteristics of this test that test takers unanimously talk about?

First of all, it can never be covered by just 1 or 2 experts!

• Meaningful learning is possible only when experts in each field provide lectures based on their specialized knowledge.

Second, we need field-specific, practice-oriented lectures!

• Since this is an exam designed to train real data analysts at a national level, it is difficult to exclude field issues from the exam.

Third, although you just need to avoid failing, you will be asked questions about specialized knowledge that non-majors do not know!

• Since the questions asked are difficult to solve for those who are not majoring in data statistics and data security, you will be closer to passing if you have a basic understanding of the relevant topics.

Fourth, the biggest obstacle to passing the written exam is none other than statistical skills!

• Statistical knowledge plays a key role in fostering the ability to understand big data and apply it in practice.
  The exam also provides a balanced assessment of your basic statistical theory and your ability to apply it to real-world problems.

  The secret to passing the exam quickly

One, Big Quarter Guide Lecture provided!

• You can pass the exam quickly if you know the whole thing. To increase learning efficiency, read the overview of big data analysis.
  We provide guided lectures on the subject.

Two, thorough analysis of past exam questions!

• The past is a mirror that reflects the future. After checking the test criteria and previous test theories, we can predict the next test theory.
  Prepare for the injury.

Set, minimize the burden of learning!

• You don't need to know every single word. This is not a lecture that explains things in detail without giving any key points, but rather a lecture that provides context.
  This is a lecture on theoretical analysis .

Nope, Analysis from the questioner's perspective!

• We select the key theories of frequent occurrence in each subject and provide persistent solutions to representative types of past questions .
  We will be your sure-fire running mate for passing the exam through analysis of past exam questions.

Use of practical textbooks written directly by professors (new book scheduled for publication in 25 years)

Expected Questions Q&A 💬

Introducing the knowledge sharers for this course.

This course was developed through joint work between the representative instructors of [Nuclear House], the brand representing RMP's certification, and [Vermind], a content expert.

Choi Ye-shin

• 1. Overview of Big Data Analysis Planning
• Information Processing Technician
• Current) Steel Association, Digital Convergence Promotion Agency-AI, Big Data Lecture
• Current) Corporate Technology Guidance (KOTERA)
• Former LG CNS Big Data Business and Technology Expert Committee Member

Kwon Tae-hyeop

• Subject 1 Big Data Analysis Planning
• Current) LG CNS Big Data Project PM
• Expert in the field of data-based information analysis and data consulting

Park Jin-won

• 2nd subject Big Data Exploration
• Current) LG CNS Data Scientist
• Majored in statistics, expert in data analysis and visualization analysis based on statistical models

Please check out the related lectures!

[Nuclear House] 2023 Big Data Analyst (Written)
Current lectures for subjects 1-2

[Nuclear House] 2023 Big Data Analyst (Written)
Subject 3-4 Next lecture