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.
提供方
IBM课程信息
830,946 次近期查看
学生职业成果
11%
通过此课程获得实实在在的工作福利
可灵活调整截止日期
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可分享的证书
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100% 在线
立即开始，按照自己的计划学习。
初级
完成时间大约为20 小时
英语（English）
字幕：阿拉伯语（Arabic）, 法语（French）, （欧洲人讲的）葡萄牙语, 意大利语, 越南语, 德语（German）, 俄语（Russian）, 英语（English）, 西班牙语（Spanish）, 波斯语
您将学到的内容有
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.
您将获得的技能
- Data Science
- Github
- Python Programming
- Jupyter notebooks
- Rstudio
学生职业成果
11%
通过此课程获得实实在在的工作福利
可灵活调整截止日期
根据您的日程表重置截止日期。
可分享的证书
完成后获得证书
100% 在线
立即开始，按照自己的计划学习。
初级
完成时间大约为20 小时
英语（English）
字幕：阿拉伯语（Arabic）, 法语（French）, （欧洲人讲的）葡萄牙语, 意大利语, 越南语, 德语（German）, 俄语（Russian）, 英语（English）, 西班牙语（Spanish）, 波斯语
提供方
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.
授课大纲 - 您将从这门课程中学到什么
完成时间为 3 小时
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.
完成时间为 3 小时
17 个视频 （总计 84 分钟）
完成时间为 10 小时
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.
完成时间为 10 小时
12 个视频 （总计 54 分钟）
完成时间为 5 小时
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.
完成时间为 5 小时
15 个视频 （总计 72 分钟）
完成时间为 2 小时
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.
完成时间为 2 小时
1 个阅读材料
审阅
- 5 stars67.11%
- 4 stars22.25%
- 3 stars6.62%
- 2 stars2.13%
- 1 star1.85%
来自TOOLS FOR DATA SCIENCE的热门评论
由 DH 提供Sep 21, 2020
Gives you a good idea and overview about different tools but can be overwhelming because of the amount of new information and some videos are not up to date. Week 3 especially had some weak videos.
由 FC 提供Nov 5, 2019
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.
由 RJ 提供Oct 7, 2021
Great course with practical approach to tools that come handy beside data science with python such as git and github, Some basic R coding and a great introduction to IBM Watson studio and cloud.
由 YK 提供Mar 24, 2020
There was a problem with the connection to R lab, never fixed. Also, some tutorials are outdated. These are the negative parts and why I give four stars. Other than that I like the course so far.
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