Artificial intelligence (AI) and machine learning (ML) have become an essential part of the toolset for many organizations. When used effectively, these tools provide actionable insights that drive critical decisions and enable organizations to create exciting, new, and innovative products and services. This course empowers you to apply various approaches and algorithms to solve business problems through AI and ML, follow a methodical workflow to develop sound solutions, and use open source, off-the-shelf tools to develop, test, and deploy those solutions, and ensure that they protect the privacy of users. Course includes an exam voucher for the Certified Artificial Intelligence Practitioner (CAIP) exam (exam AIP-110).
In this course, you will implement AI techniques in order to solve business problems. You will:
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.
Build classification models.
Build clustering models.
Build decision trees and random forests.
Build support-vector machines (SVMs).
Build artificial neural networks (ANNs).
Promote data privacy and ethical practices within AI and ML projects.