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.
このコースについて
836,640 最近の表示
受講生の就業成果
38%
コース終了後に新しいキャリアをスタートした
39%
コースが具体的なキャリアアップにつながった
21%
昇給や昇進につながった
共有できる証明書
修了時に証明書を取得
100%オンライン
自分のスケジュールですぐに学習を始めてください。
柔軟性のある期限
スケジュールに従って期限をリセットします。
初級レベル
約19時間で修了
英語
字幕：英語, 韓国語
受講生の就業成果
38%
コース終了後に新しいキャリアをスタートした
39%
コースが具体的なキャリアアップにつながった
21%
昇給や昇進につながった
共有できる証明書
修了時に証明書を取得
100%オンライン
自分のスケジュールですぐに学習を始めてください。
柔軟性のある期限
スケジュールに従って期限をリセットします。
初級レベル
約19時間で修了
英語
字幕：英語, 韓国語
提供：
IBM
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.
シラバス - 本コースの学習内容
4時間で修了
Data Scientist's Toolkit
This week, 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.
4時間で修了
17件のビデオ （合計84分）
17件のビデオ
Languages of Data Science2 分
Introduction to Python3 分
Introduction to R Language3 分
Introduction to SQL3 分
Other Languages6 分
Categories of Data Science Tools2 分
Open Source Tools for Data Science - Part 17 分
Open Source Tools for Data Science - Part 25 分
Commercial Tools for Data Science5 分
Cloud Based Tools for Data Science8 分
Libraries for Data Science4 分
Application Programming Interfaces (API)4 分
Data Sets - Powering Data Science6 分
Sharing Enterprise Data - Data Asset eXchange3 分
Machine Learning Models7 分
The Model Asset Exchange5 分
4の練習問題
Practice Quiz - Languages 30 分
Practice Quiz - Tools30 分
Practice Quiz - Packages, APIs, Data Sets, Models30 分
Graded Quiz30 分
9時間で修了
Open Source Tools
This week, 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.
9時間で修了
12件のビデオ （合計66分）
12件のビデオ
GitHub - Getting Started3 分
GitHub - Working with Branches5 分
Git and GitHub via command line (Optional)9 分
Branching and merging via command line (Optional)5 分
Contributing to repositories via pull request (Optional)8 分
Getting Started with Jupyter Notebook5 分
Getting Started with JupyterLab6 分
Jupyter Architecture6 分
What is RStudio IDE?4 分
Installing Packages and Loading Libraries in RStudio IDE2 分
Plotting Within RStudio IDE3 分
4の練習問題
Practice Quiz - GitHub30 分
Practice Quiz - Jupyter Notebook30 分
Practice Quiz - RStudio IDE30 分
Graded Quiz30 分
4時間で修了
IBM Tools for Data Science
This week, 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.
4時間で修了
15件のビデオ （合計72分）
15件のビデオ
Watson Studio Introduction4 分
Creating an Account on IBM Watson Studio2 分
Jupyter Notebook in Watson Studio - Part 1 2 分
Jupyter Notebook in Watson Studio - Part 23 分
Linking GitHub to Watson Studio2 分
Other IBM Tools for Data Science1 分
IBM Watson Knowledge Catalog6 分
Data Refinery7 分
SPSS Modeler Flows in Watson Studio6 分
IBM SPSS Modeler7 分
SPSS Statistics7 分
Model Deployment with Watson Machine Learning4 分
Auto AI in Watson Studio4 分
IBM Watson OpenScale7 分
3の練習問題
Practice Quiz - Watson Studio30 分
Practice Quiz - Other IBM Tools30 分
Graded Quiz30 分
3時間で修了
Final Assignment: Create and Share Your Jupyter Notebook
This week, 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.
3時間で修了
1 学習用教材
1件の学習用教材
IBM Digital Badge2 分
レビュー
TOOLS FOR DATA SCIENCE からの人気レビュー
CBにより2018年11月1日
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.
GCにより2020年4月12日
It serves perfecty its aim that is giving a first glance of the open course tools for data science. Of course each tool is briefly touched and it hands over the student the duty to deepen each tool.
NKにより2019年5月19日
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.
RRにより2019年4月24日
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!!!!
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