What are some of the most popular data science tools, how do you use them, and what are their features? In this course, you'll learn about Jupyter Notebooks, JupyterLab, RStudio IDE, Git, GitHub, and Watson Studio. You will learn about what each tool is used for, what programming languages they can execute, their features and limitations. With the tools hosted in the cloud on Skills Network Labs, you will be able to test each tool and follow instructions to run simple code in Python, R or Scala. To end the course, you will create a final project with a Jupyter Notebook on IBM Watson Studio and demonstrate your proficiency preparing a notebook, writing Markdown, and sharing your work with your peers.
제공자:
IBM이 강좌에 대하여
최근 조회 713,719회
학습자 경력 결과
13%
가 이 강좌를 통해 확실한 경력상 이점을 얻음
유동적 마감일
일정에 따라 마감일을 재설정합니다.
공유 가능한 수료증
완료 시 수료증 획득
100% 온라인
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
초급 단계
완료하는 데 약 18시간 필요
영어
자막: 아랍어, 프랑스어, 포르투갈어 (유럽), 이탈리아어, 베트남어, 독일어, 러시아어, 영어, 스페인어, 페르시아어
배울 내용
Describe the languages, tools, and data used by data scientists, including IBM tools focused on data science.
Describe the features of Jupyter Notebook and RStudio IDE that make them popular for data science projects.
Create and manage source code for data science in GitHub.
Explain how IBM Watson Studio and other IBM data science tools can be used by data scientists.
귀하가 습득할 기술
Data ScienceGithubPython ProgrammingJupyter notebooksRstudio
학습자 경력 결과
13%
가 이 강좌를 통해 확실한 경력상 이점을 얻음
유동적 마감일
일정에 따라 마감일을 재설정합니다.
공유 가능한 수료증
완료 시 수료증 획득
100% 온라인
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
초급 단계
완료하는 데 약 18시간 필요
영어
자막: 아랍어, 프랑스어, 포르투갈어 (유럽), 이탈리아어, 베트남어, 독일어, 러시아어, 영어, 스페인어, 페르시아어
제공자:
IBM
IBM is the global leader in business transformation through an open hybrid cloud platform and AI, serving clients in more than 170 countries around the world. Today 47 of the Fortune 50 Companies rely on the IBM Cloud to run their business, and IBM Watson enterprise AI is hard at work in more than 30,000 engagements. IBM is also one of the world’s most vital corporate research organizations, with 28 consecutive years of patent leadership. Above all, guided by principles for trust and transparency and support for a more inclusive society, IBM is committed to being a responsible technology innovator and a force for good in the world.
강의 계획 - 이 강좌에서 배울 내용
완료하는 데 3시간 필요
Data Scientist's Toolkit
In this module, you will get an overview of the programming languages commonly used, including Python, R, Scala, and SQL. You’ll be introduced to the open source and commercial data science tools available. You’ll also learn about the packages, APIs, data sets and models frequently used by data scientists.
완료하는 데 3시간 필요
17개 동영상 (총 84분)
완료하는 데 10시간 필요
Open Source Tools
In this module, you will learn about three popular tools used in data science: GitHub, Jupyter Notebooks, and RStudio IDE. You will become familiar with the features of each tool, and what makes these tools so popular among data scientists today.
완료하는 데 10시간 필요
12개 동영상 (총 54분)
완료하는 데 4시간 필요
IBM Tools for Data Science
In this module, you will learn about an enterprise-ready data science platform by IBM, called Watson Studio. You'll learn about some of the features and capabilities of what data scientists use in the industry. You’ll also learn about other IBM tools used to support data science projects, such as IBM Watson Knowledge Catalog, Data Refinery, and the SPSS Modeler.
완료하는 데 4시간 필요
15개 동영상 (총 72분)
완료하는 데 1시간 필요
Final Assignment: Create and Share Your Jupyter Notebook
In this module, you will demonstrate your skills by creating and configuring a Jupyter Notebook. As part of your grade for this course, you will share your Jupyter Notebook with your peers for review.
완료하는 데 1시간 필요
1 개의 읽기 자료
검토
TOOLS FOR DATA SCIENCE의 최상위 리뷰
CB 제공2018년 11월 1일
Tools are fantastic and will make a significant contribution to my education. Videos need to be updated for changes to Watson Studios. Support from IBM on their cloud services should also be improved.
NK 제공2019년 5월 19일
The course video contents and the tools versions are not the same.There are some significant differences .Videos should be updated.In general the course is a good fundamental course about the tools.
FC 제공2019년 11월 5일
It would be nice if you could update the material since some tools have changed either name or the way they look compared to the videos/images. Very good material though, I enjoyed the course much.
AJ 제공2020년 9월 15일
Absolutely Loved this course!! Challenging at times to keep up with all the terms and processes. The course provided great insight into Data Science. Would highly recommend it as your first course.
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