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

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!

(4.3) 19 reviews

404 learners

  • lmy0016004
자격증
시험
Big Data

Reviews from Early Learners

What you will learn!

  • Course 1: Big Data Analysis Planning Core Theory

  • Chapter 2: Big Data Exploration Core Theory

  • Useful tips from a working data scientist

  • Analysis of past questions and final special lectures provided

  • Advanced Fighter Statistics Special Lecture to Help You Pass the Exam

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 💬

Q. Is this an exam that non-majors can also take?

Yes! If you fall into any of the following categories, you can take this exam.

  1. University graduates or those expected to graduate (regardless of major)
  2. A person who graduated from a 3-year college or university and has at least one year of work experience after graduation (regardless of major or job field)
  3. A person who graduated from a two-year vocational college and has at least two years of work experience after graduation (regardless of major or job field)
  4. A person who has acquired qualifications of a knight rank or higher (regardless of the subject)
  5. Those who have completed or are expected to complete a technical training course at the article level (regardless of subject)
  6. A person who has acquired a qualification of industrial engineer level or higher and has work experience of more than 1 year (regardless of industry or job field)
  7. A person who has completed an industrial technician level technical training course and has at least 2 years of work experience after completion (regardless of industry or job field)
  8. A person who has acquired qualifications of a technician level or higher and has at least 3 years of work experience (regardless of subject or job field)
  9. People with more than 4 years of work experience (regardless of job field)

And, generally, the qualification of a technician is matched with those who have obtained a bachelor's degree from a university. "Big Data Analysis Technician" is an exam that certifies a bachelor's level or higher to be able to analyze big data, and it is an exam that anyone can pass if they are interested and study.

Q. I don't plan on taking the exam, but I'm interested in developing my data capabilities. Will this help?

Yes! If you want to become a complete technical expert, you will need to study and work much harder, but if your goal is to become a person with data analysis capabilities, you can get a lot of help with your current studies.

Q. Why are data analysis capabilities important?

Data analysis skills are key to corporate decision-making, and are an important element that job seekers and employees who need to drive work performance should cultivate.


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!

Recommended for
these people

Who is this course right for?

  • For those who want to obtain a Big Data Analysis (Written) Certification

  • Those preparing for employment or career change in data analysis positions

  • Those who want to study data analysis

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Answers

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Curriculum

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40 lectures ∙ (17hr 36min)

Course Materials:

Lecture resources
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Reviews

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19 reviews

4.3

19 reviews

  • hblee95105950님의 프로필 이미지
    hblee95105950

    Reviews 1

    Average Rating 5.0

    5

    100% enrolled

    I am leaving a review after reading the 5th Big Data Analysis article. (Total 4 subjects) First of all, all instructors explain the contents of the lecture well to grasp the concepts. They especially focus on concepts that appear in high-frequency problems. As a disadvantage, some lectures follow the recommended book's progress and the order is slightly changed (not all). Also, the recommended book is focused on many mock exams rather than detailed explanations, making it difficult to solve the problems. You have to get answers through questions. On the other hand, there were additional concepts that were introduced for reference considering the lecture time among the concepts that are not in the book, which was confusing. In addition, the reason why you have to listen to PART 3 and 4 instead of this lecture is that you have to listen to the explanation at least in PART 3 to understand. However, you can memorize PART 4. This is related to the difficulty of the exam. Lastly, since the Big Data Analysis Engineer exam is also a test for engineers, I recommend that you only watch the lectures to the extent of asking and answering questions and understanding the concepts (don't just skip over them) rather than listening to the lectures repeatedly, and memorize the concepts of the problems that appear in the mock exams or exams.

    • lmy0016004
      Instructor

      Hello HBL! Thank you so much for leaving a valuable review after the exam. In the case of this course, the curriculum was designed with the learning system in mind, so there are some parts that are a little different from the table of contents of the recommended books. I ask for your understanding and hope that you have good results! We will treasure your opinions and try to reflect them in the development of the next course. Thank you!

  • cromtaewon4339님의 프로필 이미지
    cromtaewon4339

    Reviews 6

    Average Rating 5.0

    5

    100% enrolled

    It was nice to be able to quickly learn about the good river and its overall structure.

    • lmy0016004
      Instructor

      Hello, Itaewon! This is Sohwakseong. Thank you for taking our course and giving us encouraging words of praise~ Monday morning!! I feel so energized!! Fighting to you too, Itaewon~

  • saintphs3015님의 프로필 이미지
    saintphs3015

    Reviews 4

    Average Rating 5.0

    5

    89% enrolled

    It's good because it seems to give you a general idea of the big topic of big data analysis.

    • lmy0016004
      Instructor

      Hello, HyoungSik Park! Thank you for leaving a valuable compliment after taking the big data course. In the case of the big data analyst, rather than learning locally, if you learn the overall context, and then understand the main theories and increase the learning difficulty of frequently appearing theories, I think it would be more efficient to learn. Based on the feedback from many of you who have taken the course, we will try to make the course a little more improved in 2023. Take care of your health during the changing seasons and have a nice day!

  • kikim752004님의 프로필 이미지
    kikim752004

    Reviews 2

    Average Rating 4.5

    4

    100% enrolled

    • oh58626597님의 프로필 이미지
      oh58626597

      Reviews 2

      Average Rating 4.5

      4

      100% enrolled

      For the first subject, it would be good if the lecture content were more structured. The analysis process and analysis procedures seem to differ only in whether they're in Korean or English, but the explanations are different, and there are several such parts throughout, which is a bit confusing as a student. Still, thanks to the instructors who summarize things later, I was able to understand it somewhat, and the second subject instructor's explanations are good.

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