Fundamentals of Artificial Intelligence
Understand how artificial intelligence works and how to apply it in real business settings. This course explains how AI systems process data, learn from examples, reason through information, and support decision-making. Follow the full AI lifecycle, from data quality considerations through machine learning, natural language processing, computer vision, and deployment challenges. Examine responsible AI principles, including fairness, transparency, security, and privacy, and evaluate how to implement AI thoughtfully within your organization.
Format
PDF Course
Course Lists
Duration
5 Hours
Course Information
Author: Steven Bragg
Course Number: SP1021
Learning Objectives
Identify the best uses for different types of neural networks.
Specify the steps included in the machine learning project lifecycle.
Describe the differences between supervised and unsupervised learning.
Identify the drawbacks of deep learning models.
Specify the different types of data used to train AI models.
Identify the different types of data augmentation.
Recall the differences between overfitting and underfitting.
Specify the solutions to overfitting and underfitting.
Describe the types of metrics that can be used to evaluate AI models.
Specify why practitioners prefer ensemble methods over single decision trees.
Specify how text vectorization works in natural language processing.
Recall the different types of text preprocessing steps.
Recall the advantages and disadvantages of word-level and character-level tokenization.
Specify the best uses for a convolutional neural network (CNN).
Identify why a CNN uses a convolutional filter to process an image.
Recall how the optical flow concept applies to computer vision.
Recall how the concept of data poisoning impacts machine learning security.
Specify how the use of proxies can lead to indirect discrimination.
Identify the reasons supporting the use of data anonymization.
Specify the actions that can be taken to protect user data privacy in AI development.
Level: Intermediate
Instructional Method: QAS Self-Study
NASBA Category: Computer Software and Applications
Prerequisites: None
Advance Preparation: None
Latest Review Date: December 2025
Program Registration Requirements: Click on the Enroll button to pay for and access the course. You will then be able to download the course as a PDF file, then take an on-line examination, and then download a certificate of completion if you pass the examination.
Program Refund Policy: For more information regarding administrative policies concerning complaints, refunds, and other matters, see our policies page.