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.
Offered By
IBM Skills NetworkAbout this Course
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Learner Career Outcomes
14%
started a new career after completing these courses
18%
got a tangible career benefit from this course
Flexible deadlines
Reset deadlines in accordance to your schedule.
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Beginner Level
Approx. 20 hours to complete
English
Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, English, Spanish, Persian
What you will learn
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.
Skills you will gain
- Data Science
- Github
- Python Programming
- Jupyter notebooks
- Rstudio
Learner Career Outcomes
14%
started a new career after completing these courses
18%
got a tangible career benefit from this course
Flexible deadlines
Reset deadlines in accordance to your schedule.
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Beginner Level
Approx. 20 hours to complete
English
Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, English, Spanish, Persian
Offered by
IBM Skills Network
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.
Syllabus - What you will learn from this course
3 hours to complete
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.
3 hours to complete
17 videos (Total 84 min)
10 hours to complete
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.
10 hours to complete
12 videos (Total 54 min)
5 hours to complete
IBM Tools for Data ScienceÂ
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.
5 hours to complete
15 videos (Total 72 min)
2 hours to complete
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.
2 hours to complete
1 reading
Reviews
- 5 stars67.07%
- 4 stars22.23%
- 3 stars6.63%
- 2 stars2.14%
- 1 star1.91%
TOP REVIEWS FROM TOOLS FOR DATA SCIENCE
by FDNov 17, 2020
Some of the lab assignments had instructions that didn't line up with how the programs actually worked. This was particularly the case for modular flow where auto-numerics seemed impossible to use.
by YKMar 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.
by DHSep 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.
by NSJun 29, 2019
This course is very nice to understand Python, Zappelin and R Studio basics on code and concepts, in which you will get hands on along with creating a free IBM Cloud and Watson Studio account.
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