• Classroom
  • Online, Instructor-Led
Course Description

Artificial Intelligence (AI) and Machine Learning (ML) have become an essential part of the toolset for data-driven organizations. When used effectively, AI/ML drives organizations to innovate and excel. Certified AI Practitioner (CAIP) equips you with a vendor-neutral, cross-industry knowledge of AI and ML concepts and skills, enabling you to propel your data career from analyst to AI practitioner.

Learning Objectives

In this course, you will develop AI solutions for business problems. You will: solve a given business problem using AI and ML, prepare data for use in machine learning, train, evaluate, and tune a machine learning model, build linear regression models, build forecasting models, build classification models using logistic regression and k -nearest neighbor, build clustering models, build classification and regression models using decision trees and random forests, build classification and regression models using support-vector machines (SVMs), build artificial neural networks for deep learning, put machine learning models into operation using automated processes, and maintain machine learning pipelines and models while they are in production.

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

  • Cybersecurity Management
  • Program/Project Management and Acquisition
  • Risk Management
  • Strategic Planning and Policy

Specialty Areas have been removed from the NICE Framework. With the recent release of the new NICE Framework data, updates to courses are underway. Until this course can be updated, this historical information is provided to give better context as to how it can help you with your cybersecurity goals.

Feedback

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