• Online, Self-Paced
Course Description

Use Python lists to analyze medical insurance cost data.

Learning Objectives

In this Aspire Journey lab, you will perform DL programming tasks with Python, such as performing series expansion and calculus, and work with Tensorflow and scikit-image. Then, test your skills by answering assessment questions after loading a data set for hierarchical clustering and k-means clustering, and train a model using random forests and gradient boosting.

This lab provides access to several tools commonly used in machine learning, including:

• Microsoft Excel 2016

• Visual Studio Code

• Anaconda

• Jupyter Notebook + JupyterHub

• Pandas, NumPy, SiPy

• Seaborn Library

• Spyder IDE

Framework Connections

The materials within this course focus on the NICE Framework Task, Knowledge, and Skill statements identified within the indicated NICE Framework component(s):

Specialty Areas

  • Software Development

Feedback

If you would like to provide feedback for this course, please e-mail the NICCS SO at NICCS@hq.dhs.gov.