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데이터 과학이란 무엇인가?

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Based on 21 ratings
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Rav Ahuja and Alex Aklson

The art of uncovering the insights and trends in data has been around since ancient times. The ancient Egyptians used census data to increase efficiency in tax collection and they accurately predicted the flooding of the Nile river every year. Since then, people working in data science have carved out a unique and distinct field for the work they do. This field is data science. In this course, we will meet some data science practitioners and we will get an overview of what data science is today.

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What's inside

Syllabus

데이터 과학 정의 및 데이터 과학자가 하는 일
이 모듈에서는 이 과정에서 학습할 내용을 알아보기 위해 과정 계획서를 살펴봅니다. 또한 데이터 과학 전문가로부터 데이터 과학의 정의, 데이터 과학자가 하는 일, 데이터 과학자가 매일 사용하는 도구 및 알고리즘에 대해 들어봅니다. 마지막으로, 문서 과제를 완료하여 데이터 과학이 21세기 가장 매력적인 직업으로 여겨지는 이유를 알아봅니다.
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Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
데이터 과학 분야에서 경력에 관심이 있는 사람에게 필요한 기술을 다룹니다
데이터 과학에 대한 기본적인 내용을 다룹니다
데이터 과학자가 주로 사용하는 도구와 알고리즘을 알아봅니다
데이터 과학자가 하는 일에 대해 자세히 살펴봅니다

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Reviews summary

데이터 과학 입문자를 위한 포괄적 개요

학습자들은 이 과정을 데이터 과학 입문자를 위한 이상적인 출발점이라고 평가합니다. 명확하고 간결한 강의 구성 덕분에 데이터 과학의 정의와 핵심 개념을 빠르게 이해할 수 있습니다. 특히 데이터 과학자의 역할과 실생활에서의 비즈니스 적용 사례에 대한 통찰은 경력 탐색에 매우 유용하다는 평입니다. 전반적으로 깔끔하고 친절한 설명으로 비전공자도 쉽게 접근할 수 있지만, 이미 관련 지식이 있는 학습자에게는 다소 내용이 얕게 느껴질 수 있으며, 실습 위주의 학습은 부족하다는 의견도 있습니다.
실제 비즈니스 환경에서의 데이터 과학 활용을 다룹니다.
"특히, 실생활 예시와 함께 설명된 데이터 과학의 비즈니스 적용 부분은 매우 유익했습니다."
"저는 데이터 분석가로 일하고 있는데, ... 비즈니스에서의 데이터 과학 적용 사례는 신선했습니다."
"데이터 과학의 정의부터 비즈니스 적용까지 큰 그림을 이해하는 데 큰 도움이 되었습니다."
복잡한 데이터 과학 개념을 쉽고 명료하게 전달합니다.
"각 모듈의 내용은 명확하고 잘 정리되어 있어 초보자도 쉽게 따라갈 수 있습니다. 강사님의 설명 방식도 친절하고 이해하기 쉬웠습니다."
"데이터 과학이라는 광범위한 분야를 단시간에 이해할 수 있도록 구성된 최고의 입문 과정입니다. 강의의 흐름이 논리적이고, 용어 설명이 친절해서 어려움 없이 수강할 수 있었습니다."
"강사님의 명료한 설명과 구체적인 사례 덕분에 재미있게 수강할 수 있었어요."
데이터 과학 분야 입문 및 경력 탐색에 이상적입니다.
"최근에 데이터 과학 분야로 커리어를 전환하기 위해 이 과정을 수강했습니다. 이 과정은 데이터 과학이 무엇인지, 데이터 과학자들이 어떤 일을 하는지, 그리고 필요한 역량에 대한 정말 훌륭한 개요를 제공합니다."
"저는 이 과정을 통해 데이터 과학 입문자에게 필요한 데이터 과학자의 일상과 현실적인 통찰을 얻을 수 있어 매우 좋았습니다."
"이 강의를 통해 데이터 과학 분야로 이직을 고민하던 저는 데이터 과학의 정의부터 비즈니스 적용까지 큰 그림을 이해하는 데 큰 도움이 되었습니다."
이론 위주의 강의로, 실질적인 핸즈온 경험은 부족합니다.
"강의 자료 자체는 깔끔하지만, 저는 좀 더 실습 위주의 내용이 추가된다면 훨씬 좋을 것 같다고 생각합니다."
"저는 실습이 거의 없는 점이 아쉬웠습니다. 이론적인 부분에 강한 강의였습니다."
"이 과정은 제목 그대로 '무엇인가?'에 대한 답만 제공하고, '어떻게 하는가?'에 대한 부분은 거의 없었습니다."
개론적인 내용에 집중하며, 기술적 깊이는 기대하기 어렵습니다.
"다만, 이미 관련 분야에 대한 지식이 있는 사람에게는 다소 내용이 얕게 느껴질 수 있습니다. 심화 학습을 위해서는 별도의 자료나 다른 과정을 찾아봐야 할 것 같아요."
"저는 데이터 과학에 대한 개론적인 내용은 잘 다루고 있다고 보지만, 실제적인 기술 습득에는 큰 도움이 되지 않아 실망했습니다. 프로그래밍이나 통계 지식을 기대했거든요."
"너무 개론적인 내용이라 기대했던 것보다는 별로였습니다. 저는 좀 더 기술적인 측면을 배우고 싶었는데, 이 과정은 그런 목적에는 맞지 않는 것 같습니다."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in 데이터 과학이란 무엇인가? with these activities:
데이터 시각화 도구 탐구
데이터 시각화 도구를 탐구하여 데이터를 이해하고 전달하는 기술을 개발합니다.
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  • Tableau 또는 Power BI와 같은 데이터 시각화 도구를 선택합니다.
  • 온라인 튜토리얼이나 강좌를 찾아 봅니다.
  • 샘플 데이터 세트를 사용하여 데이터 시각화를 만듭니다.
  • 도구 기능을 탐구하고 시각화 옵션을 실험합니다.
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Career center

Learners who complete 데이터 과학이란 무엇인가? will develop knowledge and skills that may be useful to these careers:
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See salaries and explore the career path for Data Scientist
Data Analyst
Data Analysts use their skills to collect, clean, and analyze data. They use this data to identify trends and patterns, and to make recommendations for businesses. This course provides an overview of data science, and the tools and algorithms that data analysts use every day. If you are interested in a career in data analysis, this course is a great place to start.
See salaries and explore the career path for Data Analyst
Machine Learning Engineer
Machine Learning Engineers use their skills to develop and deploy machine learning models. These models can be used to solve a variety of problems, such as fraud detection, natural language processing, and image recognition. This course provides an overview of data science, and the tools and algorithms that machine learning engineers use every day. If you are interested in a career in machine learning engineering, this course is a great place to start.
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Data Engineer
Data Engineers use their skills to design and build data pipelines. These pipelines are used to collect, clean, and store data. This course provides an overview of data science, and the tools and algorithms that data engineers use every day. If you are interested in a career in data engineering, this course is a great place to start.
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Business Analyst
Business Analysts use their skills to analyze business data and identify opportunities for improvement. They use this information to make recommendations for businesses. This course provides an overview of data science, and the tools and algorithms that business analysts use every day. If you are interested in a career in business analysis, this course is a great place to start.
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Statistician
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Market Researcher
Market Researchers use their skills to collect, analyze, and interpret data about markets. They use this information to make recommendations for businesses. This course provides an overview of data science, and the tools and algorithms that market researchers use every day. If you are interested in a career in market research, this course is a great place to start.
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Financial Analyst
Financial Analysts use their skills to analyze financial data and make recommendations for investors. This course provides an overview of data science, and the tools and algorithms that financial analysts use every day. If you are interested in a career in financial analysis, this course is a great place to start.
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Operations Research Analyst
Operations Research Analysts use their skills to analyze data and make recommendations for improving the efficiency of operations. This course provides an overview of data science, and the tools and algorithms that operations research analysts use every day. If you are interested in a career in operations research, this course is a great place to start.
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Data Visualization Specialist
Data Visualization Specialists use their skills to create visual representations of data. These visualizations can be used to communicate insights and trends to stakeholders. This course provides an overview of data science, and the tools and algorithms that data visualization specialists use every day. If you are interested in a career in data visualization, this course is a great place to start.
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Database Administrator
Database Administrators use their skills to manage and maintain databases. This course provides an overview of data science, and the tools and algorithms that database administrators use every day. If you are interested in a career in database administration, this course is a great place to start.
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Reading list

We've selected nine books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in 데이터 과학이란 무엇인가?.
Cover image
Data Science for Business
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Provides a comprehensive overview of data science, including its history, methods, and applications. It valuable resource for anyone who wants to learn more about data science, regardless of their background.
(English) Data Science for Business: What You Need to Know...
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(English) Data Science for Business: What You Need to Know...
Kindle Edition
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Deep Learning
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Provides a comprehensive overview of deep learning, covering topics such as convolutional neural networks, recurrent neural networks, and generative adversarial networks. It valuable resource for students and practitioners who want to learn the theoretical foundations of deep learning.
(English) Deep Learning
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(English) Deep Learning (Adaptive Computation and Machine...
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(English) Deep Learning (Adaptive Computation and Machine...
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Python for Data Analysis
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Provides a comprehensive introduction to Python for data analysis, covering topics such as data manipulation, data visualization, and statistical modeling. It valuable resource for beginners who want to learn the basics of data science using Python.
(English) Python for Data Analysis: Data Wrangling with...
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(English) Python for Data Analysis
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(English) Python for Data Analysis: Data Wrangling with...
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Hadoop: The Definitive Guide
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Hadoop 생태계에 대한 포괄적인 가이드북으로, 데이터 과학 프로젝트에서 대규모 데이터를 처리하는 데 필요한 지식을 습득하는 데 도움이 됩니다.
(English) Hadoop: The Definitive Guide: Storage and Analysis...
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(English) Hadoop: The Definitive Guide
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(English) Hadoop: The Definitive Guide
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(English) Hadoop: The Definitive Guide
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The Elements of Statistical Learning
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Provides a comprehensive overview of statistical learning methods and is considered a foundational text for understanding the more advanced topics in data science.
(English) The Elements of Statistical Learning: Data Mining,...
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(English) The Elements of Statistical Learning: Data Mining,...
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(English) The Elements of Statistical Learning: Data Mining,...
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Data Science from Scratch
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Provides a hands-on introduction to data science, using Python. It valuable resource for anyone who wants to learn more about data science, regardless of their background.
(English) Data Science from Scratch: First Principles with...
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(English) Data Science from Scratch: First Principles with...
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(English) Data Science from Scratch: First Principles with...
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Information Visualization
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데이터 시각화의 인지적 원리를 다루는 책으로, 데이터 과학에서 시각화의 효과적인 사용을 이해하는 데 도움이 됩니다.
(English) Information Visualization: Perception for Design...
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(English) Information Visualization: Perception for Design...
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Information Visualization (Interactive...
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(English) Information Visualization: Perception for Design...
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(English) Information Visualization: Perception for Design...
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Read, Write, Think Data
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Tableau를 사용하여 데이터를 효과적으로 시각화하고 전달하는 데 대한 가이드북으로, 데이터 과학 결과를 이해하기 쉽게 제시하는 데 도움이 됩니다.
(English) Read, Write, Think Data: A Step-by-Step Guide to...
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(English) Read, Write, Think Data: A Step-by-Step Guide to...
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Artificial Intelligence For Dummies
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For non-technical readers who want a broad overview of data science concepts without too much technical jargon. It covers a wide range of topics, including data collection, analysis, and visualization.
(English) Artificial Intelligence For Dummies (For Dummies...
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(English) Artificial Intelligence For Dummies (For Dummies...
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(English) L'Intelligence artificielle Pour les Nuls, NE
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(English) Artificial Intelligence For Dummies
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Rating
4.5 Filled star Filled star Filled star Filled star Half star
Effort
5 hours to complete
Level
Introductory
Via
Coursera
Institution
IBM
Instructors
Rav Ahuja
Alex Aklson
Language
한국어
Transcript
English
Traffic lights
Read about what's good
what should give you pause
and possible dealbreakers
데이터 과학 분야에서 경력에 관심이 있는 사람에게 필요한 기술을 다룹니다
데이터 과학에 대한 기본적인 내용을 다룹니다
데이터 과학자가 주로 사용하는 도구와 알고리즘을 알아봅니다
데이터 과학자가 하는 일에 대해 자세히 살펴봅니다
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