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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.
Register for this course and see more details by visiting:
OpenCourser.com/course/qpwzru/deiteo
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.
Read more
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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데이터 과학 주제
이 모듈에서는 New York University의 Stern Center for Research Computing 학부장인 Norman White가 데이터 과학과 이 분야에서 경력을 쌓는 데 관심이 있는 사람에게 필요한 기술에 대해 이야기하고, 데이터 과학 분야에서 경력을 시작하려는 사람들에게 조언을 제공합니다. 마지막으로, 문서 과제를 완료하여 주어진 데이터 세트를 마이닝하는 과정과 회귀 분석에 대해 학습해야 합니다.
비즈니스에서의 데이터 과학
이 모듈에서는 기업이 데이터 과학을 시작하기 위해 무엇을 해야 하는지에 대해 배웁니다. 데이터 과학자를 다른 전문가와 구별하는 몇 가지 자질에 대해서도 배우게 됩니다. 또한 분석과 이 프로세스에서 데이터 과학자가 수행하는 중요한 역할, 스토리텔링 및 효과적인 최종 결과물의 중요성에 대해 배우게 됩니다. 마지막으로 주관식 질문에 답하여 데이터 과학에 대해 배운 내용을 적용해야 합니다.
Good to know
Good to know
Know what's good ,
what to watch for , 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
Save this course
Save 데이터 과학이란 무엇인가? to your list so you can find it easily later:
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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
Show steps
데이터 시각화 도구를 탐구하여 데이터를 이해하고 전달하는 기술을 개발합니다.
Browse courses on
Tableau
Show steps
-
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.
Show all one activities
데이터 시각화 도구 탐구
Show steps
데이터 시각화 도구를 탐구하여 데이터를 이해하고 전달하는 기술을 개발합니다.
Browse courses on
Tableau
Show steps
Show steps
Show steps
- 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.
Show all one activities
Career center
Learners who complete 데이터 과학이란 무엇인가? will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
Data Science is the art of extracting insights and trends from data. Data Scientists use their skills to solve problems and make informed decisions. This course provides an overview of what data science is today and the tools and algorithms that data scientists use every day. If you are interested in a career in data science, this course is a great place to start.
Data Analyst
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.
Machine Learning Engineer
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.
Data Engineer
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.
Business Analyst
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.
Statistician
Statistician
Statisticians use their skills to collect, analyze, and interpret data. They use this information to make inferences about the world around us. This course provides an overview of data science, and the tools and algorithms that statisticians use every day. If you are interested in a career in statistics, this course is a great place to start.
Market Researcher
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.
Financial Analyst
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.
Operations Research Analyst
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.
Data Visualization Specialist
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.
Database Administrator
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.
Software Engineer
Software Engineer
Software Engineers use their skills to design, develop, and maintain software systems. This course provides an overview of data science, and the tools and algorithms that software engineers use every day. If you are interested in a career in software engineering, this course is a great place to start.
Computer Scientist
Computer Scientist
Computer Scientists use their skills to study the theory and practice of computer science. This course provides an overview of data science, and the tools and algorithms that computer scientists use every day. If you are interested in a career in computer science, this course is a great place to start.
Data Architect
Data Architect
Data Architects use their skills to design and build data architectures. This course provides an overview of data science, and the tools and algorithms that data architects use every day. If you are interested in a career in data architecture, this course is a great place to start.
Actuary
Actuary
Actuaries use their skills to assess risk and uncertainty. This course provides an overview of data science, and the tools and algorithms that actuaries use every day. If you are interested in a career in actuarial science, this course is a great place to start.
For more career information including salaries, visit:
OpenCourser.com/course/qpwzru/deiteo
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?.
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.
Save
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.
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.
Hadoop 생태계에 대한 포괄적인 가이드북으로, 데이터 과학 프로젝트에서 대규모 데이터를 처리하는 데 필요한 지식을 습득하는 데 도움이 됩니다.
Provides a comprehensive overview of statistical learning methods and is considered a foundational text for understanding the more advanced topics in data science.
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.
데이터 시각화의 인지적 원리를 다루는 책으로, 데이터 과학에서 시각화의 효과적인 사용을 이해하는 데 도움이 됩니다.
Tableau를 사용하여 데이터를 효과적으로 시각화하고 전달하는 데 대한 가이드북으로, 데이터 과학 결과를 이해하기 쉽게 제시하는 데 도움이 됩니다.
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.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/qpwzru/deiteo
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Effort
3 weeks of study, 2-3 hours/week
Level
Introductory
Via
Coursera
Institution
IBM
Instructors
Rav Ahuja
Alex Aklson
Language
한국어
Transcript
English
Good to know
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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