• Online, Self-Paced
Course Description

In this Aspire Journey lab, you will perform ML programming tasks with Python, such as splitting data and standardizing data, and classification using nearest neighbors and ridge regression. Then, test your skills by answering assessment questions after performing principle component analysis, visualizing correlations, training a naïve Bayes model and a support vector machine model.

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

Learning Objectives

In this Aspire Journey lab, you will perform ML programming tasks with Python, such as splitting data and standardizing data, and classification using nearest neighbors and ridge regression. Then, test your skills by answering assessment questions after performing principle component analysis, visualizing correlations, training a naïve Bayes model and a support vector machine model.

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

  • Systems Architecture