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.
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.
Syllabus
Syllabus - What you will learn from this course
Week 1
Data Scientist’s Toolkit
Week 2
Open Source Tools
Week 3
IBM Tools for Data Science
Week 4
Final Assignment: Create and Share Your Jupyter Notebook
FAQ
When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
What will I get if I subscribe to this Certificate?
When you enroll in the course, you get access to all of the courses in the Certificate, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
Reviews
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 Also, some tutorials are outdated.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.
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.
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.
Good introductory course to the tools. Hands-on labs are fascinating. Sometimes I got a little lost with too much terminology, but at the end of the lessons the most important points were clear.
