2025년 데이터 분석을 배울 수 있는 최고의 온라인 리소스-(강좌, 서적, 유튜브 등) 데이터 과학

 

오늘날은 매일 수많은 데이터가 생성되는 데이터 시대입니다. Facebook '좋아요' 하나만 클릭해도 데이터가 생성됩니다. 따라서 매일 생성되는 데이터의 양이 얼마나 많은지 상상할 수 있습니다. 따라서 방대한 양의 데이터에서 유용한 정보를 찾아내기 위해 데이터 분석가가 등장합니다. 그렇기 때문에 데이터 분석가는 수익성이 높고 안전하며 가장 까다로운 직업입니다. 하지만 대부분의 사람들은 어디서부터 배워야 할지 몰라 막막해합니다. 그래서 데이터 분석을 배울 수 있는 최고의 온라인 리소스를 모두 모아서 결합해 보려고 생각했습니다.

 

이 글에서는 데이터 분석을 배울 수 있는 최고의 온라인 강좌, 튜토리얼, 책, YouTube 튜토리얼을 찾을 수 있습니다.

 

몇 분만 투자하여 데이터 분석을 배울 수 있는 최고의 온라인 리소스를 찾아보세요. 이 글을 북마크에 추가하여 나중에 이 글을 참조할 수 있습니다.

 

이제 더 이상 고민할 필요 없이 시작해 보겠습니다. 

 

 

 

 

 

Table Of Contents

1. Skills Required for Data Analysis-
   • 1. Programming
   • 2. Statistics
   • 3. Mathematics
   • 4. Data Wrangling
   • 5. Data visualization
   • 6. Machine Learning
2. Resources to learn Data Analysis
   • Online Courses
   • Text Books
   • Tutorials
   • YouTube Videos
3. Conclusion

Best Online Resources to Learn Data Analysis

Before discussing the resources, I would like to tell you what topics or skills you need to learn for data analysis-

Skills Required for Data Analysis-

1. Programming

Programming knowledge is a must-have skill for a Data Analyst. This is the core skill that makes a Data analyst apart from Business Analyst. You must know one or more programming languages like Python, R, or SAS.

Along with that, you should be familiar with data science libraries and packages (such as ggplot2, reshape2, NumPy, pandas, and scipy). Knowledge of all programming languages is not required. You can choose any language.

2. Statistics

To become a successful data analyst, you should know Statistics. Statistics knowledge will give you the ability to decide which algorithm is good for a certain problem.

Statistics knowledge includes statistical tests, distributions, and maximum likelihood estimators. All are essential in data analysis.

3. Mathematics

As a data analyst, you have to deal with numbers. That’s why strong knowledge of Math is required. You should be familiar with multivariate calculus and linear algebra. Along with that, you should have an understanding of matrix manipulations, dot products, eigenvalues and eigenvectors, and multivariable derivatives.

4. Data Wrangling

Data wrangling is all about data collection and data cleaning. So, for that, you should know about database systems- both SQL-based and NoSQL-based. You should also be familiar with relational databases such as PostgreSQL, MySQL, Netezza, and Oracle, as well as Hadoop, Spark, and MongoDB.

5. Data visualization

As a Data Analyst, you have to showcase your findings in a visual form, so that stakeholders can understand them properly. This is an important step for a Data Analyst. That’s why the knowledge of Data Visualization is important. And for that, you should be familiar with data visualization tools like ggplot, matplotlib, Seaborn, and D3.js.

You should know various Reporting tools like Tableau and power bi. These tools have in-built visualization reporting tools. By drag and drop, you can create a wonderful presentation report.

6. Machine Learning

After having all previous skills, it’s good to have a basic knowledge of Machine Learning. Not all Data Analysts have Machine Learning knowledge, but if you want to get the extra privilege, it’s better to have Machine Learning skills.

You don’t need to learn the theory and implementation details behind all ML algorithms. All you need to know is its pros and cons, as well as when to and when not to apply these algorithms to a dataset. 

So, these are some must-have skills for Data Analysis, now let’s move to the Best Online Resources to Learn Data Analysis.

Resources to learn Data Analysis

For your convenience, I have created separate tables for each resource. So let’s start with online courses-

Online Courses

Topics	Online Courses
1. Data Analysis-	1. Become a Data Analyst– Udacity 2. Intro to Data Analysis– (Free Course) Udacity 3. Data Science Specialization– Johns Hopkins University 4. SQL for Data Analysis– (Free Course) Udacity 5. Data Analysis with R– (Free Course) Udacity 6.  IBM Data Science Professional Certificate.– IBM 7. Data Analysis and Visualization– (Free Course) Udacity 8.  Applied Data Science with Python Specialization– University of Michigan 9. Data Analyst Masters Program– Edureka
2. Programming language	1. Python for Everybody – University of Michigan 2. Introduction To Python Programming– Udemy 3. Python Core and Advanced– Udemy 4. Crash Course on Python– Google 5. Python for Absolute Beginners!– Udemy 6. Introduction to Python Programming– Udacity 7. Python 3 Programming Specialization– University of Michigan 8. R Programming – Johns Hopkins University 9. Programming for Data Science with R– Udacity 10. R Programming A-Z™– Udemy
3. Statistics	1. Intro to Statistics (Free Course) Udacity 2. Statistics with R Specialization– Duke University 3. Statistics with Python Specialization– University of Michigan 4. Intro to Inferential Statistics– (Free Course) Udacity 5. Intro to Descriptive Statistics– (Free Course) Udacity 6. Data Science: Statistics and Machine Learning Specialization– Johns Hopkins University 7. Basic Statistics– University of Amsterdam 8. Statistical Analysis with R for Public Health Specialization–Imperial College London 9. Business Statistics and Analysis Specialization– Rice University 10. Statistics for Data Science and Business Analysis– Udemy 11. Intro to Statistics– Udacity
4. Mathematics	1. Mathematics for Machine Learning Specialization– Imperial College London 2. Mathematics for Data Science Specialization– Coursera 3. Data Science Math Skills– Duke University 4. Intro to Statistics– Udacity 5. Probability – The Science of Uncertainty and Data– MITx 6. Basic Statistics– University of Amsterdam 7. Probabilistic Graphical Models Specialization– Stanford University 8. Introduction to Calculus– The University of Sydney 9. Probability and Statistics– University of London
5. Data Wrangling	1. Learn SQL– Udacity 2.  Excel to MySQL: Analytic Techniques for Business Specialization– Duke University 3.  Learn SQL Basics for Data Science Specialization– University of California, Davis 4.  Databases and SQL for Data Science– IBM 5. Modern Big Data Analysis with SQL Specialization– Cloudera 6. Introduction to Structured Query Language (SQL)– University of Michigan 7. Data Warehousing for Business Intelligence Specialization– University of Colorado System 8. SQL Essentials Training & Certification- Edureka 9. The Complete SQL Bootcamp 2025– Udemy 10. SQL – MySQL for Data Analytics and Business Intelligence- Udemy
6. Data visualization	1. Data Visualization with Tableau Specialization– University of California, Davis 2. Data Visualization with Advanced Excel– PwC 3. Data Visualization in Tableau– Udacity 4.  Information Visualization Specialization– New York University 5. Data Visualization with Python– IBM 6. Data Visualization and Communication with Tableau– Duke University 7. Data Visualization– Coursera 8. Tableau 2025 Certified Associate Exam Guide A-Z (w Datasets)– Udemy 9. Complete Tableau 2025 Training for Absolute Beginners– Udemy
7. Machine Learning	1.  Become a Machine Learning Engineer  (Udacity) 2. Machine Learning– Stanford University 3. Machine Learning with Python– IBM 4. Intro to Machine Learning with TensorFlow  (Udacity) 5. Machine Learning A-Z™: Hands-On Python & R In Data Science -Udemy 6. Python for Data Science and Machine Learning Bootcamp– Udemy 7. Advanced Machine Learning Specialization– Coursera

Text Books

Topics	Text Books
1. Programming Language	1. Python Crash Course by Eric Matthes Buy on Amazon. 2. Head First Python: A Brain-Friendly Guide by Paul Barry Buy on Amazon. 3. Learn Python the Hard Way by Zed A. Shaw  Buy on Amazon. 4. Automate the Boring Stuff with Python by Al Sweigart  Buy on Amazon. 5. R for Data Science by Hadley Wickham Buy on Amazon. 6. Machine Learning with R by Brett Lantz  Buy on Amazon 7. The Book of R: A First Course in Programming and Statistics by Tilman M. Davies Buy on Amazon.
2. Statistics	1. An Introduction to Statistical Learning by Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani Buy this book on Amazon-An Introduction to Statistical Learning You can download the pdf version of this book from here. 2. Practical Statistics for Data Scientists by Peter Bruce Buy this book on Amazon-Practical Statistics for Data Scientists 3. Probability and Statistics for Data Science by Norman Matloff Buy this book on Amazon-Probability and Statistics for Data Science. 4. The Art of Statistics: How to Learn from Data by David Spiegelhalter Buy this book on Amazon or download the PDF here. 5. How to Lie with Statistics by Darrell Huff Buy this book on Amazon or download the PDF here.
3. Mathematics	1. Introduction to Probability by Joseph K. Blitzstein, Jessica Hwang Buy this book on Amazon- Introduction to Probability. You can download the pdf version of this book from here. 2. Mathematics for Machine Learning by Marc Peter Deisenroth Buy on Amazon. 3. Linear Algebra and Optimization for Machine Learning by Charu C. Aggarwal Buy on Amazon or check the table of content from here.
4. Data Wrangling	1. The Data Wrangling Workshop by Brian Lipp Buy on Amazon. 2. Hands-On Data Analysis with Pandas: Efficiently perform data collection, wrangling, analysis, and visualization using Python by Stefanie Molin Buy on Amazon 3. Data Analysis From Scratch With Python by  Peters Morgan 4. Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython by Wes McKinney Buy on Amazon.
5. Data Visualization	1. Storytelling with Data: A Data Visualization Guide for Business Professionals by Cole Nussbaumer Knaflic Buy on Amazon 2. Data Visualization: A Practical Introduction by Kieran Healy Buy on Amazon or download the PDF here. 3. Effective Data Visualization: The Right Chart for the Right Data by Stephanie Evergreen Buy on Amazon. 4. Data Visualisation: A Handbook for Data-Driven Design by Andy Kirk  Buy on Amazon or download the PDF here.
6. Machine Learning	1. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow by Aurélien Géron Buy on Amazon 2. The Hundred-Page Machine Learning Book by Andriy Burkov  Buy on Amazon. 3. Machine Learning For Absolute Beginners by  Oliver Theobald Buy on Amazon 4. Machine Learning: An Applied Mathematics Introduction by Paul Wilmott Buy on Amazon

Tutorials

Topics	Tutorials
1. Programming Language	1. The Python Tutorial (PYTHON.ORG) 2. Python 3 Tutorial (SOLOLEARN) 3. Python Tutorial- MLTUT 4. LEARNPYTHON.ORG 5. Google’s Python Class 6. Python Tutorial (AFTER HOURS PROGRAMMING) 7. Python Tutorial- Tutorials Point 8. Python Tutorial– W3Schools 9. R Tutorial- Tutorials Point 10. R Tutorial- Statmethods
2. Statistics	1. Statistics and probability– Khan Academy 2. Statistics – Probability (TutorialsPoint) 3. Probability and Statistics (MathisFun) 4. Statistics Tutorial- TutorialsPoint 5. STATISTICS TUTORIALS: BEGINNER TO ADVANCED– Listen Data
3. Mathematics	1. Probability on Khan Academy 2. Probability Tutorial (Stat Trek) 3. Probability theory (Wikipedia) 4. Introduction to Calculus (MathisFun) 5. Calculus 1 on Khan Academy
4. Data Wrangling	1. Python – Data Wrangling– TutorialsPoint 2. Python Data Wrangling Guide- Noble Desktop 3. Python Data Wrangling Tutorial: Cryptocurrency Edition– Elite Data Science 4. Data Wrangling with pandas Cheat Sheet
5. Data Visualization	1. Tableau Tutorial– JavatPoint 2. Data Visualization– TutorialsPoint 3. Tableau Tutorial– Tableau.com 4. Data Visualisation with Tableau– DataCamp
6. Machine Learning	1. Machine Learning with Python Tutorial- Tutorials Point 2. Machine Learning Basics– MLTUT 3. Machine Learning Tutorial- Javatpoint 4. Machine Learning– GeeksforGeeks

YouTube Videos

Topics	YouTube Videos
1. Programming Language	1. CS DOJO 2. Programming with Mosh 3. Telusko 4. Clever Programmer 5. Corey Schafer 6. R Programming Tutorial– freeCodeCamp.org 7. R Programming Full Course– Simplilearn
2. Statistics	1. Statistics for Data Science– Great Learning 2. Statistics – A Full University Course on Data Science Basics–freeCodeCamp.org 3. Statistics for Data Science Course– Intellipaat 4. Statistics Course for Data Science | Statistics Course– MarinStatsLectures-R Programming & Statistics
3. Mathematics	2. Mathematics for Machine Learning [Full Course]– Edureka 3. Mathematics For Machine Learning- Simplilearn 4. Mathematics for Machine Learning– My CS
4. Data Wrangling	1. Machine Learning Data Pre-processing & Data Wrangling using Python– The AI University 2. Data Wrangling: dplyr– OHI-Science
5. Data Visualization	1. Data Visualization with D3.js – Full Tutorial Course- freeCodeCamp.org 2. Data Visualization Tutorial For Beginners- Simplilearn 3. Data Visualization Tutorial– by Krish Naik 4. Intro to Data Visualization with R & ggplot2– Data Science Dojo 5. Seaborn python tutorial | Data Visualization Using Python Seaborn– Great Learning 6. Tableau Full Course– Edureka 7. Power BI Tutorial From Beginner to Pro– Avi Singh – PowerBIPro
6. Machine Learning	1. Machine Learning with Python– Great Learning 2. Machine Learning Tutorial Python– codebasics 3. Python Machine Learning Tutorial- Programming with Mosh 4. Machine Learning by Krish Naik

And here the list ends. I hope these resources will definitely help you to learn and master data analysis. I would suggest you bookmark this article for future referrals. Now it’s time to wrap up.

Conclusion

In this article, I tried to cover all the Best Online Resources to Learn Data Analysis from online courses to YouTube videos. If you have any doubts or questions, feel free to ask me in the comment section.

All the Best!

Enjoy Learning!

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