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, RStudio IDE, Apache Zeppelin and Data Science Experience. 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 Cognitive Class 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 Data Science Experience and demonstrate your proficiency preparing a notebook, writing Markdown, and sharing your work with your peers.
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提供：
IBM
33,615 登録済み
シラバス - 本コースの学習内容
週
13時間で修了
Introducing Skills Network Labs
This week, you will get an overview of the various data science tools available to you, hosted on Skills Network Labs. You will create an account and start exploring some of the features.
3 readings, 4 quizzes
3件の学習用教材
What is Skills Network Labs?10 分
Account Features10 分
Creating an account.10 分
2の練習問題
Practice Quiz2 分
Quiz 1 - Skills Network Labs30 分
2時間で修了
Jupyter Notebooks
This week, you will learn about a popular data science tool, Jupyter Notebooks, its features, and why they are so popular among data scientists today.
2件のビデオ （合計6分）, 4 quizzes
1の練習問題
Quiz 2 - Jupyter Notebooks30 分
週
23時間で修了
Apache Zeppelin Notebooks
This week, you will learn about Apache Zeppelin Notebooks, its feature, and how they are different from Jupyter Notebooks.
3件のビデオ （合計11分）, 3 quizzes
1の練習問題
Quiz 3 - Zeppelin Notebooks30 分
3時間で修了
RStudio IDE
This week, you will learn about a popular data science tool used by R programmers. You'll learn about the user interface and how to use its various features.
4件のビデオ （合計12分）, 3 quizzes
4件のビデオ
Uploading files, Installing packages and loading libraries in RStudio IDE3 分
Getting started with RStudio IDE4 分
RStudio Environment and History3 分
1の練習問題
Quiz 4 - RStudio IDE30 分
週
34時間で修了
IBM Watson Studio
This week, you will learn about an enterprise-ready data science platform by IBM, called Watson Studio (formerley known as Data Science Experience). You'll learn about some of the features and capabilities of what data scientists use in the industry.
4件のビデオ （合計10分）, 2 readings, 2 quizzes
4件のビデオ
Creating an account on IBM Watson Studio (Data Science Experience)1 分
Jupyter notebooks on Watson Studio (Data Science Experience) - Part 1/23 分
Jupyter Notebooks on IBM Watson Studio (Data Science Experience) - Part 2/24 分
2件の学習用教材
Preface: What is IBM Watson Studio (formerly Data Science Experience)?5 分
Lab - IBM Watson Studio
1の練習問題
Quiz 5 - IBM Watson Studio30 分
3時間で修了
Project: Create and share a Jupyter Notebook
1 reading, 1 quiz
1件の学習用教材
IBM Digital Badge2 分
4.6
673件のレビュー43%
コース終了後に新しいキャリアをスタートした
42%
コースが具体的なキャリアアップにつながった
22%
昇給や昇進につながった
人気のレビュー
To the contrast of other reviews, I find the content very well bifurcated and fed to the learners. The course very easily digestable and I have had a great amount of fun learning it.. Go for it!!!!
All the tools required for ML kick starting was explained very clearly and it helped me a lot in building the understanding of what tools need to be learnt in the field of ML and Data Science.
講師
Polong Lin
Data ScientistIBM Developer Skills Network
IBMについて
IBM offers a wide range of technology and consulting services; a broad portfolio of middleware for collaboration, predictive analytics, software development and systems management; and the world's most advanced servers and supercomputers. Utilizing its business consulting, technology and R&D expertise, IBM helps clients become "smarter" as the planet becomes more digitally interconnected. IBM invests more than $6 billion a year in R&D, just completing its 21st year of patent leadership. IBM Research has received recognition beyond any commercial technology research organization and is home to 5 Nobel Laureates, 9 US National Medals of Technology, 5 US National Medals of Science, 6 Turing Awards, and 10 Inductees in US Inventors Hall of Fame.
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