Online AI Product Manager Training Course | Udacity
This course guides product managers through the application of AI and machine learning in business. The curriculum begins with an overview of AI and machine learning, their industry applications, and terminology, including supervised and unsupervised learning and neural networks. The course then explores how AI can be used to build successful products, including identifying suitable business cases and forming effective AI product teams. Data's crucial role in model performance is highlighted, with instructions on creating labeled datasets using Appen's annotation platform. The practical aspect of the course is emphasized through a project involving the creation of a medical image annotation job using Appen's platform. Participants are taught model training strategies, both from scratch and through transfer learning, as well as evaluation techniques using tools like AutoML. A hands-on experience with Google AutoML is provided, building a classification model for chest x-ray images. The course concludes with a focus on measuring model impact and mitigating bias, including strategies for scaling AI products. A case study on video annotation demonstrates the complete AI product development cycle, from ideation to launch and continuous improvement. The final project challenges learners to design and propose a complete AI product, considering users, data, design, and iterative development.
Welcome!
Welcome to this course on AI for Product Managers! Learn about the course structure and resources available to you.
Introduction to AI and Machine Learning
Get an overview of AI and machine learning and where they are used in industry. This lesson covers terminology and applications of supervised learning, unsupervised learning, and neural networks.
Using AI and Machine Learning in Business
How do you build a successful AI product? Learn which kinds of narrow business cases can stand to benefit the most from machine learning, and identify the components of an effective, AI product team.
Data Fit and Annotation
Learn how data can affect the performance of a machine learning model and see how to create your own labeled dataset using Appen's annotation platform.
Project: Create a Medical Image Annotation Job
Given a dataset and business goal, design your own data labeling job using Appen’s platform.
Training and Evaluating a Model
Learn strategies for training a model from scratch or using transfer learning. Evaluate a model using machine learning tools, such as AutoML.
Build a Model with Google AutoML
Build a classification model to classify images of chest xrays using Google AutoML, an automated machine learning tool.
Introduction to Measuring Impact and updating Models
Introduction to the Measuring Impact and Updating Models course.
Measuring Business Impact & Mitigating Bias
Learn best practices for measuring model success, strategies for mitigating unwanted bias in a model, and scaling an AI product so that it's available to a large audience.
Case Study: Video Annotation
Review an end-to-end, AI product development cycle from solution ideation to prototyping and testing and finally, product launch (and continuous improvement) for a video annotation product.
Project: Creating an AI Product Business Proposal
Complete a proposal for a complete AI product of your own design; consider users, data source, design practices, and iteration over time.