• Online, Self-Paced
Course Description

Explore critical machine learning (ML) and deep learning concepts and the various categorizations of algorithms and their implementations using Python.

Learning Objectives

AI and ML Solutions with Python: Machine Learning and Data Analytics

  • describe the core concepts of machine learning
  • identify the critical features and comparable features of machine learning and deep learning
  • recognize the correlation and comparable features of machine learning and AI
  • set up the development environment for machine learning using Python
  • list the various types and techniques of analytics
  • identify the essential benefits of predictive and descriptive analytics
  • define the various data metrics that are used to quantify the data for analytics
  • classify the various algorithms used in supervised learning
  • demonstrate how to implement regression algorithm
  • load data set, create data frames, and print the shape of data frames

Framework Connections

The materials within this course focus on the Knowledge Skills and Abilities (KSAs) identified within the Specialty Areas listed below. Click to view Specialty Area details within the interactive National Cybersecurity Workforce Framework.