Bespoke Datasets for Multimodal AI Products

Overview

This course is for product managers who want to build AI products that include multimodal data such as text, video, and audio. Leveraging existing data for AI applications is a great way to get started, but bespoke datasets can offer improved accuracy, domain specificity, and, ultimately, a competitive advantage. The course starts with an overview of supervised machine learning techniques, computer vision—the technology that allows computers to "see"—and how computer vision and supervised ML can be combined. Then, you'll learn more about how to create bespoke datasets for computer vision and other applications, and conclude with a walkthrough of the key stakeholders involved in AI product development. In the project, you'll develop a roadmap for an AI-powered video creation app.

Syllabus

Supervised Machine Learning and Computer Vision

Dive deeper into each step of the supervised machine learning process, from data understanding to model evaluation, then learn how to combine these approaches with computer vision technology

Data Annotation for AI Products

Learn how data can affect the performance of an AI system and determine whether a bespoke dataset is needed, then practice developing a data annotation plan

AI Stakeholders and Roadmaps

Collaborate with stakeholders, enhance communication, and develop roadmaps for AI products. Develop skills in influencing without authority and the RICE prioritization framework.