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):
Competency Areas
Feedback
If you would like to provide feedback on this course, please e-mail the NICCS team at NICCS@mail.cisa.dhs.gov. Please keep in mind that NICCS does not own this course or accept payment for course entry. If you have questions related to the details of this course, such as cost, prerequisites, how to register, etc., please contact the course training provider directly. You can find course training provider contact information by following the link that says “Visit course page for more information...” on this page.