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.
- Data Scientist’s Toolkit.
- Open Source Tools.
- IBM Tools for Data Science.
- Final Assignment: Create and Share Your Jupyter Notebook.
What you will learn
- Describe the languages, tools, and data used by data scientists, including IBM tools focused on data science.
- Create and manage source code for data science in GitHub.
- Describe the features of Jupyter Notebook and RStudio IDE that make them popular for data science projects.
- Explain how IBM Watson Studio and other IBM data science tools can be used by data scientists.