This course covers how to apply various approaches and algorithms to solve business problems through AI and ML, follow a methodical workflow to develop sound solutions, use open source, off-the-shelf tools to develop, test, and deploy those solutions, and ensure that they protect the privacy of users.
Learning Objectives
Students will implement AI techniques in order to solve business problems. Students will learn to specify a general approach to solve a given business problem that uses applied AI and ML, collect and refine a dataset to prepare it for training and testing, train and tune a machine learning model, finalize a machine learning model and present the results to the appropriate audience, build linear regression models, classification models, clustering models, decision trees and random forests, support-vector machines and artificial neural networks, and will learn to promote data privacy and ethical practices within AI and ML projects.
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
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