Overview
Artificial Intelligence Solutions: An Introductory View from a Human-Machine Perspective includes 10 modules that are completely online and can be taken at your own pace. Each module includes videos, suggested reading materials, quizzes and exams.
Each module is graded as pass/fail. To receive a pass grade for the course, you must receive a score of 70% or higher on the quizzes and exam for each module. The entire course should take approximately 12 hours to complete. After the successful completion of this course, you’ll receive a certificate certifying your achievement.
Course Learning Outcomes
Upon successful completion of the course, students will be able to:
- Convert a problem of interest into a human-centered AI solution.
- Define solutions in terms of knowledge representations, necessary data, and goals to establish appropriate expectations for the solution.
- Find and curate relevant data sets for an AI solution.
- Outline strengths and weaknesses of AI techniques for human-centered solutions to identify an appropriate technique for a given problem.
- Distinguish between rule-based and statistical techniques, applying them to human-centered problems in data science, computer vision, health, language processing, and cybersecurity.
- Identify appropriate evaluation metrics for different problems and quantify an AI solution’s strengths and weaknesses.
Course Modules
- Module 0 – Course Introduction
- Module 1 – AI Solution Elements
- Module 2 – Knowledge-Based AI
- Module 3 – Data Acquisition and Annotation
- Module 4 – Statistical Learning I
- Module 5 – Statistical Learning II
- Module 6 – AI Applied to Health
- Module 7 – AI Applied to Cyber I
- Module 8 – AI Applied to Cyber II
- Module 9 – Evaluation Approaches