Tools for Data Science

Module 1: Overview of Data Science Tools

This module introduces the various categories of Data Science tools, including open source, commercial, and cloud-based tools. You will also explore the learning goals of the course and engage in practice and graded quizzes to reinforce your understanding of the tools.

Module 2: Languages of Data Science

Delve into the essential programming languages used in Data Science, such as Python, R, and SQL. This module provides an introduction to each language and explores other languages commonly utilized in the field. Engage in practice and graded quizzes to solidify your language skills.

Module 3: Packages, APIs, Datasets, and Models

Discover libraries for Data Science, application programming interfaces (APIs), data sets, and machine learning models. You will also explore additional sources of datasets and gain hands-on experience with the Model Asset eXchange and the Data Asset eXchange. Engage in practice and graded quizzes to reinforce your understanding of these essential components.

Module 4: Jupyter Notebooks and JupyterLab

Gain a comprehensive understanding of Jupyter Notebooks and JupyterLab, including their architecture, kernels, and various environments. Engage in practice and graded quizzes, as well as hands-on labs, to solidify your knowledge and skills in using Jupyter for Data Science.

Module 5: RStudio & GitHub

Explore the use of R and RStudio for Data Science, including data visualization and working with GitHub for source code management. This module provides in-depth coverage of R basics, GitHub repositories, and branching. Engage in practice quizzes and hands-on labs to enhance your proficiency in RStudio and GitHub.

Module 6: Create and Share your Jupyter Notebook

This module encompasses the creation and sharing of a Jupyter Notebook, showcasing your proficiency in preparing a notebook, writing Markdown, and sharing your work with peers.

Module 7: [Optional] IBM Watson Studio

For those interested, this optional module introduces IBM Watson Studio, providing insights into creating a Watson Studio project with Jupyter Notebooks and linking GitHub to Watson Studio. Engage in a practice quiz and assignment using Watson Studio to expand your knowledge of this platform.