Build 10 AI projects in 10 days without coding using Google Teachable Machines, DataRobot, AWS Autopilot, and Vertex AI
The curriculum is organized into 10 distinct days, each centered around a specific machine learning task or tool, following a pattern of project overview, data exploration, training, and deployment.
Instruction includes specific lessons on evaluating models using KPIs such as Confusion Matrices, Precision vs. Recall, and Regression metrics like Mean Squared Error.
Editorial course preview
These 4 complementary views highlight concrete, legible examples from the course presentation.
A split-screen frame displays a presenter alongside a title card for Day 5, which outlines a project to develop a machine learning model for predicting used car prices using DataRobot.
A split-screen layout featuring a title card for Day 9 regarding credit card default prediction with AWS SageMaker Autopilot alongside a presenter speaking to the camera.
A split-screen view featuring an instructor on the right and a title card on the left announcing Day 2 of the course, which focuses on deep diving into AI technicalities like hyperparameters.
A split-screen view featuring a presenter alongside a title card for Day 4, which outlines the topic of visualizing state-of-the-art artificial intelligence models using specific tools.
Learner signals indicate that the DataRobot interface has changed significantly, making lecture examples difficult to replicate. Additionally, reports suggest a lack of available trial versions for this tool.
One signal suggests early material contains significant repetition. Another indicates missing links or data required to complete specific assessments.
The curriculum aligns with the goal of teaching no-code AI to non-programmers through various platforms.
