Overview

Build confident Canvas teaching and administration with one clear, end to end guide. Canvas can feel scattered when course design, grading, analytics, SIS feeds, AI tools and governance all live in different places. Instructors try to keep courses consistent, while administrators worry about data quality, access controls and outages. This book brings those pieces together. It shows you how Canvas actually works as a platform, how to design clean courses, how to connect SIS and data pipelines, and how to use analytics and AI features in ways that are realistic, auditable and sustainable. Design stable course shells with the right settings, term dates, navigation and home pages. Structure content with modules, pages, assignments, discussions, quizzes and Mastery Paths that students can follow without confusion. Use Gradebook, SpeedGrader, rubrics, outcomes and the Learning Mastery Gradebook to make grading transparent and efficient. Turn New Analytics, engagement metrics and early alert patterns into practical outreach plans for at risk learners. Work with native AI features such as discussion summaries, rubric assistance and intelligent insights while applying clear governance rules. Configure root accounts, subaccounts, roles, permissions and feature options so instructors have power where it helps and not where it creates risk. Provision users, courses, sections and enrollments with SIS CSV files, safe import strategies, rollback plans and monitored SIS jobs. Automate tasks with the Canvas REST API using concrete examples for users, enrollments, courses, grades and pagination aware reporting. Use Canvas Data 2 and DAP with CLI tools and warehouse friendly schemas to build institutional dashboards and early alert models. Manage LTI tools, AI extensions, developer keys and scopes so integrations are secure, supportable and aligned with privacy expectations. Run large enrollment courses, heavy gradebooks and busy discussion spaces with patterns that protect performance and operational reliability. Embed accessibility, captions, alt text, course quality rubrics and prepublish review processes into everyday teaching practice. The book also includes a professional setup checklist for new courses and terms, along with practical support playbooks for SIS imports, authentication issues, LTI failures, Blueprint syncs, AI feature rollout and other recurring operational incidents. Because it is a code heavy guide, you get working CSV layouts, API calls, CLI usage and SQL style warehouse patterns that translate directly into real Canvas automation and analytics projects in your own environment. Grab your copy today and build a Canvas ecosystem that supports teaching, analytics and AI at a professional standard.

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