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데이터 과학자의 도구 상자

Jeff Leek, PhD, Brian Caffo, PhD, and Roger D. Peng, PhD

이 과정에서는 데이터 과학자의 도구 상자에 있는 메인 도구와 아이디어를 소개합니다. 본 과정은 데이터 분석가와 데이터 과학자가 작업하는 데이터, 질문 및 도구의 개요에 대해 설명합니다. 이 과정에는 두 가지 구성 요소가 있습니다. 첫 번째는 데이터를 실행 가능한 지식으로 바꾸는 아이디어에 대한 개념적 소개입니다. 두 번째는 버전 관리, 마크다운, git, GitHub, R 및 RStudio와 같은 프로그램에서 사용할 도구에 대한 실용적인 소개입니다.

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Syllabus

데이터 과학 기초

이 모듈에서는 데이터 과학과 데이터 자체를 소개하고 정의합니다. 또한 문제가 발생했을 때 데이터 과학자가 도움을 받기위해 사용하는 일부 리소스에 대해서도 살펴봅시다.

R 및 RStudio

이 모듈에서는 R 및 RStudio를 시작하고 실행하는 데 도움을 줍니다. 그 과정에서 두 가지 모두에 대한 몇 가지 기본 사항과 데이터 과학자가 이를 사용하는 이유를 학습합니다.

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適合한 대상: 데이터 분석 및 데이터 과학 분야의 초보자

데이터 과학자에게 필수적인 도구와 아이디어 소개

버전 관리, git, R, RStudio와 같은 실무적 도구 사용법 학습

강사진으로 유명한 전문가 포함

Accredited institutes, bootcamps, 실습과 유사한 실습 제공

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Reviews summary

데이터 과학 기초 도구 및 워크플로우

학생들은 이 과정이 데이터 과학 입문자에게 탁월한 출발점이라고 말합니다. R, RStudio, Git, GitHub, R Markdown과 같은 핵심 도구를 체계적이고 명확하게 소개하여, 데이터 과학 워크플로우에 대한 탄탄한 기초를 다질 수 있다고 평가합니다. 특히 실습 위주의 구성과 명확한 강사 설명이 개념 이해와 실무 적용에 큰 도움을 주었다는 의견이 많습니다. 일부 학습자는 기술 환경 설정에 어려움을 겪었지만, 최근 리뷰에서는 설치 과정이 개선되었다는 긍정적인 변화도 언급됩니다. 반면, 이미 경험이 있는 학습자에게는 내용이 다소 기초적일 수 있으며, 심화 학습이 필요하다는 의견도 있습니다. 전반적으로 데이터 과학의 첫걸음을 떼려는 이들에게 강력히 추천되는 과정입니다.

데이터 과학 입문자에게 적합하며, 경험자에게는 다소 기초적입니다.

"저는 어느 정도 경험이 있어서 그런지 일부 내용은 다소 기초적으로 느껴졌습니다. 더 깊이 있는 내용이나 고급 활용법을 기대한다면 다른 과정과 병행해야 할 것 같습니다."

"너무 기본적인 내용만 다루고 있어서 이미 알고 있는 부분이 많았어요. 간단한 소개 수준에 머물렀습니다."

"초급자에게는 강력히 추천합니다."

강사의 설명이 명확하고 실습 위주로 구성되어 이해를 돕습니다.

"강사님의 설명도 명확하고 따라하기 쉬웠습니다. 개인적으로 실습 위주의 구성이 좋았고, 직접 코드를 작성하며 배우는 것이 효과적이었습니다."

"강의 자체는 명확했지만, 실습 환경 구축에 대한 더 많은 가이드가 있었으면 좋겠습니다."

"친절한 설명과 실용적인 예시들이 인상 깊었습니다."

R, Git, GitHub, R Markdown 등 필수 도구 사용법을 익힙니다.

"R, RStudio, Git, GitHub, R Markdown과 같은 필수 도구를 체계적으로 소개해 주어 전반적인 데이터 과학 워크플로우를 이해하는 데 큰 도움이 되었습니다."

"특히 R과 Git의 기본 개념과 사용법을 배우는 데 유용했습니다."

"데이터 과학자가 갖춰야 할 핵심 역량을 효과적으로 배울 수 있었습니다. 강의 자료도 잘 정리되어 있습니다."

데이터 과학의 핵심 도구를 체계적으로 소개하여 기초를 다집니다.

"이 과정은 데이터 과학 초보자에게 매우 훌륭한 출발점입니다."

"데이터 과학을 시작하려는 사람들에게 이보다 더 좋은 과정은 없을 겁니다."

"저는 이 과정을 통해 R과 Git에 대한 막연한 두려움을 없앨 수 있었습니다. 단계별 설명이 정말 좋았습니다."

일부 학습자는 초기 환경 설정에 어려움을 겪었으나, 최근 개선되었습니다.

"과정 내용은 나쁘지 않지만, R 설치나 Git 환경 설정에서 기술적인 문제를 겪었습니다. 초보자에게는 진입 장벽이 될 수 있을 것 같아요."

"최근 업데이트된 내용 덕분인지, 설치 과정이 많이 매끄러워졌습니다. 예전 리뷰에서 환경 설정의 어려움을 언급한 것을 봤는데, 지금은 매우 쉽게 따라할 수 있었어요."

"온라인 포럼에서 도움을 받았지만, 초보자에게는 진입 장벽이 될 수 있을 것 같아요."

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 과학자의 도구 상자 with these activities:

Review R and RStudio

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Reviewing R and RStudio will help you refresh your understanding of the basic concepts, data structures, and functions used in the course.

Browse courses on R

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Install R and RStudio
Review the basics of R syntax
Practice loading and manipulating data in R

Join a study group for the course

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Joining a study group can help you learn from others, get help with difficult concepts, and stay motivated.

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Find a study group
Attend study group meetings regularly
Participate in discussions and ask questions

Follow tutorials on data cleaning and wrangling

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Following tutorials on data cleaning and wrangling will help you develop the skills necessary to prepare data for analysis.

Browse courses on Data Cleaning

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Find a tutorial on data cleaning and wrangling
Follow the tutorial step-by-step
Practice the techniques on your own dataset

Four other activities

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Solve practice problems on data analysis and visualization

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Solving practice problems will help you develop your analytical skills and ability to communicate your findings visually.

Browse courses on Data Analysis

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Find a set of practice problems
Solve the problems on your own
Check your answers and learn from your mistakes

Create a data visualization project

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Creating a data visualization project will help you learn how to effectively communicate data insights to others.

Browse courses on Data Visualization

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Choose a dataset and a visualization type
Prepare the data for visualization
Create the visualization
Write a report or presentation explaining your findings

Mentor a new student in the course

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Mentoring a new student can help you reinforce your understanding of the course material and develop your leadership skills.

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Find a new student to mentor
Meet with your mentee regularly
Provide guidance and support

Contribute to an open-source data science project

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Contributing to an open-source data science project can help you gain experience with real-world data science tools and techniques.

Browse courses on Collaborative Learning

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Find an open-source data science project
Identify a way to contribute
Make your contribution

Career center

Learners who complete 데이터 과학자의 도구 상자 will develop knowledge and skills that may be useful to these careers:

Actuary

Actuaries use data to help assess and manage risks. They work with a variety of data sources and techniques to create models that can help organizations make informed decisions about risk. This course may be useful for Actuaries as it can help them develop their data analysis skills, which will allow them to build and maintain better models.

See salaries and explore the career path for Actuary

Data Analyst

Data Analysts are responsible for collecting, cleaning, and analyzing data to find meaningful insights. They are able to use their findings to create useful reports that can be used to improve a business's decision making. This course may be useful for Data Analysts as it can help them develop skills in data management, modeling, and data visualization.

See salaries and explore the career path for Data Analyst

Statistician

Statisticians collect, analyze, interpret, and present data. They help businesses make informed decisions by providing insights into data trends and patterns. This course may be useful for Statisticians as it can help them develop skills in data management, modeling, and data visualization.

See salaries and explore the career path for Statistician

Data Engineer

Data Engineers are responsible for building and maintaining the infrastructure that supports data analysis. They work with a variety of technologies, including databases, data warehouses, and cloud computing, to ensure that data is available to data scientists and data analysts in a timely and efficient manner. This course may be useful for Data Engineers as it can help them develop skills in data management and data visualization.

See salaries and explore the career path for Data Engineer

Machine Learning Engineer

Machine Learning Engineers are responsible for building and maintaining machine learning models. They work with a variety of machine learning algorithms and techniques to create models that can solve a variety of business problems. This course may be useful for Machine Learning Engineers as it can help them develop their data analysis skills, which will allow them to build and maintain better machine learning models.

See salaries and explore the career path for Machine Learning Engineer

Data Architect

Data Architects are responsible for designing and building the data architecture for an organization. They work with a variety of data sources and technologies to create a data architecture that meets the needs of the organization. This course may be useful for Data Architects as it can help them develop their data analysis skills, which will allow them to design and build better data architectures.

See salaries and explore the career path for Data Architect

Operations Research Analyst

Operations Research Analysts use data to help improve the efficiency of business operations. They work with a variety of data sources and techniques to create models that can help businesses optimize their processes. This course may be useful for Operations Research Analysts as it can help them develop their data analysis skills, which will allow them to build and maintain better models.

See salaries and explore the career path for Operations Research Analyst

Data Scientist

A Data Scientist's primary role is to help make business decisions using data. They work with a company's raw data and use techniques from computer science, statistics, and mathematics to build models to help maximize a business's success. This course may be useful for Data Scientists as it can help them enhance their skills in data management, modeling, and data visualization.

See salaries and explore the career path for Data Scientist

Research Analyst

Research Analysts are responsible for gathering and analyzing data to provide insights to clients. They work with a variety of data sources and techniques to create reports and presentations that can help clients make informed decisions. This course may be useful for Research Analysts as it can help them develop their data analysis skills, which will allow them to provide better insights to clients.

See salaries and explore the career path for Research Analyst

Business Analyst

Business Analysts work at the intersection of business and IT. They are responsible for bridging the gap between the two divisions by translating business requirements into technical requirements. This course can help Business Analysts as it provides them with a more thorough understanding of data analysis, which will allow them to better interact with Data Scientists and Data Analysts.

See salaries and explore the career path for Business Analyst

Risk Analyst

Risk Analysts are responsible for identifying and assessing risks to an organization. They work with a variety of data sources and techniques to create models that can help organizations mitigate risks. This course may be useful for Risk Analysts as it can help them develop their data analysis skills, which will allow them to identify and assess risks more effectively.

See salaries and explore the career path for Risk Analyst

Financial Analyst

Financial Analysts use data to help make investment recommendations. They are responsible for analyzing financial data, such as company reports, economic indicators, and market trends, and making recommendations on how to invest money. This course may be useful for Financial Analysts as it can help them develop skills in data management, modeling, and data visualization.

See salaries and explore the career path for Financial Analyst

Software Engineer

Software Engineers are responsible for designing, developing, and maintaining software systems. They work with a variety of programming languages and technologies to create software that meets the needs of users. This course may be helpful for Software Engineers as it can help them develop their data analysis skills, which will allow them to design and develop better software systems.

See salaries and explore the career path for Software Engineer

Product Manager

Product Managers are responsible for the development and launch of new products. They work with a variety of stakeholders, including engineers, designers, and marketers, to ensure that products meet the needs of customers. This course may be helpful for Product Managers as it can help them develop their data analysis skills, which will allow them to make better decisions about product development.

See salaries and explore the career path for Product Manager

Quantitative Analyst

Quantitative Analysts use data to help make investment decisions. They are responsible for analyzing financial data, such as company reports, economic indicators, and market trends, and making recommendations on how to invest money. This course may be useful for Quantitative Analysts as it can help them develop skills in data management, modeling, and data visualization.

See salaries and explore the career path for Quantitative Analyst

Reading list

We've selected 11 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 과학자의 도구 상자.