A current professional data analysis instructor at a large company who passed the Big Data Analysis Writer and Practical exams in one go will help you prepare quickly by summarizing the key points.
It's a good lecture. It's good to listen to it while summarizing it one by one, since it only picks out the important things! Thank you for the good lecture.
5.0
채진욱
67% enrolled
Okay, it's good to catch the test feeling.
5.0
Hyun-jong Noh
100% enrolled
Thank you for the great lecture.
What you will gain after the course
Introduction to Big Data Analysis Reporter Exam
Reproducing the big data analysis article test environment
Data Analysis Using R
The trend is big data analysis engineers! Latest data qualification, challenge yourself properly.
Know-how proven by passing the latest big quarter!
Big data analyst?
The Big Data Analyst certification administered by the Korea Data Industry Promotion Agency is a new certification established in 2020. It is the latest nationally recognized certification with high demand for fostering and verifying big data analysis experts at the government level.
This is a course to prepare for the Big Data Analyst practical exam, a nationally recognized qualification course, using R. For prospective examinees who are having difficulty preparing because there is not much information about the exam yet, we will first ✌️pass✌️ and share the know-how!
Who would benefit from hearing this?
Pass the Big Quarter written exam Take the practical test with R Those who are preparing
Big Quarterly Practical Exam I want to prepare in advance People who do it
ADP, ProDS, DATA, etc. Data Analysis Practical Qualification Course Those who are preparing
Only for this lecture Check out the benefits.
The core content fast
faithful Examination know-how
For the single-person household Provides past exam questions
From basic grammar to statistics, machine learning, and practical examples, we'll quickly go over the key content needed to prepare for the Big Data Analyst qualification course. We'll give you a 👉point out👈 breakdown of what's being asked on the practical exam for each topic!
I will tell you more detailed information than the 🏆 Practical Exam Taking (Passing) Review🏆 that I experienced while taking the practical exam. However, not all statistical analysis and machine learning techniques in the scope of the exam are covered.
Instead! We cover 4 sets of past exam questions (12 questions total) to help you prepare well for the exam. If you can write the answer code for the relevant example without any separate reference materials, I think you will definitely pass👨🎓.
The following content I am learning.
1. Introduction to the Test
We review not only R but also Python's exam criteria and suggest test preparation strategies.
We will guide you through how to recreate the test environment so that you can prepare more systematically.
2. Data preprocessing
Review the most important content by topic to prepare for the exam.
Learn the most efficient code to produce results.
3. Statistics
We will focus on the somewhat difficult interpretation of hypothesis testing results and carefully go over them to avoid mistakes when submitting your exam answers.
4. Machine Learning
Quickly review representative algorithms for each subject area, including classification/regression/clustering analysis.
5. Past exam questions
We help you prepare systematically for the exam with 4 sets of sample questions by type that meet the exam criteria.
Created this course Introducing the knowledge sharer.
Kim Seung-wook
I majored in business analytics for my master's degree at UNIST and started data analytics. I started working in the data analytics team from my first career, and I am currently constantly working on outsourcing related to data analytics in addition to corporate/school lectures. 😎
I passed the Big Data Analyst exam on the second try, which was essentially a one-time exam.
History
Corporate lectures: Samsung Group, Shinhan Group, Hana Financial Group, SK Group, LG Electronics, GS Caltex, S-oil, etc.
University lectures: Sookmyung Women's University, Sungkyunkwan University, Kyungnam University, Seoul Women's University, Sangmyung University, etc.
Writing related: Give me some R (author), Efficient R Programming (co-translation), Doing Data Science (translation review)
No, but it will be quite helpful for exam preparation by providing strategies and precautions for each type.
Please check!
Any unauthorized distribution or use of any material provided through the Inflearn platform for commercial purposes may be subject to punishment under relevant laws. Please be aware! 🔒
For external lecture requests or inquiries: contact@rloha.io
Recommended for these people
Who is this course right for?
Those who are applying for a big data analysis position with R
If you are curious about the Big Data Analysis Technician practical environment
[Current] CEO of Rloha [Current] IT Team Lead at EpicWorks [Former] Data Analysis Team Lead at MMMD [Former] Researcher at Connectum [Former] Data Analysis Team Engineer at NBT [Former] Researcher at the Korea Meteorological Administration Big Data Team
I primarily lecture on data analysis for Samsung Group affiliates. Accumulated corporate and university lecture time exceeds 8,000 hours. (As of 2025.12) contact@rloha.io
I primarily conduct data analysis lectures for Samsung Group affiliates.
Over 8,000 cumulative hours of corporate and university lectures. (As of Dec 2025)
Analysis Team Engineer [Former] Researcher at the Korea Meteorological Administration Big Data Team. Primarily lectures on data analysis for Samsung Group affiliates. Over 8,000 cumulative hours of corporate and university lecturing. (As of Dec 2025)
It was a really helpful lecture.
I usually write code in a sloppy way while searching, but this lecture teaches you how to write code in a practical way.
It's a good lecture. It's good to listen to it while summarizing it one by one, since it only picks out the important things! Thank you for the good lecture.