inflearn logo
Challenge
Ended

Mastering Data Preprocessing with R – Complete Conquest for Immediate Practical Use Part 2 #BigDataAnalysisCertificationPracticalExam

This course is not just about simple theory; it focuses on solving data problems repeatedly encountered in actual work. It will help you develop practical skills to systematically refine dirty or complex data and efficiently process even large-scale datasets. After taking this course, you will experience the following changes: - You will be able to confidently clean any form of unstructured or structured data. - You will be able to process large-scale data efficiently using R. - You will be able to build an entire analysis workflow, from data preprocessing to visualization. - You will be able to drastically reduce work time by automating repetitive preprocessing tasks. - You will be able to secure code templates that can be applied immediately to your work. Furthermore, this course is designed to help you prepare for the R proficiency required for the Big Data Analysis Certification, allowing you to handle both practical work and exam preparation simultaneously.

Data Engineering
Data literacy

5회 미션 수행

질문하고 즉시 답을 얻어요.

aha30005480님과 함께해요!

Career Verified

Data Analysis · AI Specialist Instructor

  • Frequent lecturer for data analysis and statistics training at corporations and public institutions

  • Full-time instructor for Big Data and AI courses at a vocational training center

  • Practical and educational expert in data analysis, statistics, and social research

  • Data analysis and statistics practice lectures based on SPSS, R, and Python

  • Operating courses to prepare for Social Survey Analyst and Big Data Analysis Certification

  • Books: Secondary Social Survey Analyst Practical (Working Type), SPSS, Descriptive Questioning & Questionnaire Design, Guminsa, Secondary Social Survey Analyst Written & Practical (Descriptive), Data Analysis Tool R Fundamental, Data Scientist Series Step 1-4, Big Data Construction for AI Analysis (Structured and Unstructured Data)

I am a professional instructor who delivers data analysis and statistics in an easy and practical way, ranging from corporate and public institution training to certification preparation.

Naver Cafe
DataAN Naver Cafe

More

Have you felt overwhelmed, not knowing where to start with data analysis?

80% of data analysis is preprocessing. No matter how many great analysis techniques you know, you cannot get meaningful results if the data is messy. This course systematically covers essential data preprocessing techniques for practical work from start to finish using R.

This is not a lecture where you simply type along with the code. You will understand why we process data this way and how it is used in practice, helping you develop true data literacy skills.


This is a course consisting only of 'missions' without live sessions or videos.


Data Preprocessing with R – Complete Mastery for Immediate Practical Use Part II

In , you will acquire techniques to transform and expand data to fit your analysis., bạn sẽ học các kỹ thuật để biến đổi và mở rộng dữ liệu sao cho phù hợp với mục đích phân tích của mình.

  • Creating new insights through derived variable generation

  • Various join methods for merging multiple datasets into one

  • Remodeling data structures to fit the purpose of analysis

  • From creating summary variables to utilizing GIS coordinate data

Recommended for these people

  • Beginners starting data analysis for the first time

  • Those who have learned R but found it difficult to apply in practice

  • Job seekers who were stuck on handling missing values and outliers

  • Graduate students and researchers who need to clean thesis or research data themselves

  • Office workers who feel the limitations of Excel and want to switch to R

Prior knowledge

No prior knowledge is required. However, if you have experience with basic R syntax and reading tabular data, you will find it even easier to follow along.


To the students

I sincerely welcome all of you who have chosen to learn despite your busy daily lives. If you have any questions while listening to the lectures, please feel free to leave them at any time. I will be with you until the very end, until the day you can handle data with confidence.

4월

30일

챌린지 시작일

2026년 4월 30일 오후 03:00

챌린지 종료일

2026년 6월 30일 오후 02:30

챌린지 커리큘럼

All

5 lectures

Course Materials:

Lecture resources

챌린지에서 배워요

  • R Data Analysis Preprocessing A to Z – The Complete Guide to Exploration, Cleaning, Merging, and Derived Variables

  • Practical R Data Preprocessing: Learning Big Data Literacy Properly from the Start

Recommended for
these people

Who is this course right for?

  • Anyone who wants to improve their data literacy and everyone who wants to derive meaningful insights from data on their own.

  • Data analysis beginners who are learning R for the first time, or those who want to work with data but don't know where to start.

Need to know before starting?

  • There are no mandatory prerequisites. However, having even a basic understanding of the following will help you follow the course more easily.

  • It is good to have a basic understanding of R, such as basic syntax, variable declaration, vectors, and data frames. (It's okay if you don't know them; we will cover them together at the beginning of the lecture.)

Reviews

Not enough reviews.
Please write a valuable review that helps everyone!

FAQs

취소 및 환불 규정
챌린지는 지식공유자가 설정한 수업 최소 정원이 충족되지 않을 경우, 폐강 안내가 고지되며 결제 내역이 자동취소됩니다.

$4.40