In this module, you will practice applying automation in real work scenarios by inserting a Task List macro, writing clear action items, and assigning ownership to teammates on a shared project page. Through hands-on tasks, you will build confidence turning plans into executable, accountable workflows that you can reuse in release preparation and everyday collaboration.

This module will help you understand how tasks created across individual pages become visible in a consolidated Task Report. You will examine the difference between where a task is written and how it is reported, focusing on the role of space scope, filters, ownership, and task status. Using realistic workplace scenarios, you will practice explaining why tasks surface automatically in a space-level report and why some tasks may not appear. By the end, you will be able to clearly describe task roll-up behavior and explain the conditions that make task reporting reliable and predictable.

This module focuses on applying task tracking skills in a practical, job-relevant workflow. You will create three tasks with due dates and confirm ownership, then open the Task Report macro to verify that those tasks appear under “My Open Tasks.” Emphasis is placed on validating task visibility using correct scope and filters, not just creating tasks. You will diagnose and correct issues when tasks do not appear as expected, reinforcing strong task hygiene. By completing a short verification log, you will demonstrate your ability to create report-ready tasks and trust the accuracy of consolidated task reporting.

In this module, you will explore why tables are essential for productivity, understand the key steps involved in creating them, and practice building a basic table using best practices.

In this module, you will create and populate a project milestones table with deliverables and deadlines, demonstrating how tables support effective tracking, planning, and project communication.

This module focuses on why templates are critical for IT and platform governance. You will examine how templates enforce fonts, colours, layouts, and structural standards at scale, and how this reduces operational risk and rework across teams.

This module shifts from understanding to execution. You will practice converting a real page into a reusable template, naming it correctly, and sharing it with the appropriate team access to support standardized workflows.

In this module, you will develop a practical understanding of what “AI” means within Confluence and how it shows up through specific features and add-ons. Rather than treating AI as a broad or abstract concept, the lesson focuses on concrete examples you are likely to encounter in their daily work, such as content suggestions and automatic summaries. You will examine how these features support productivity, what problems they are designed to solve, and how to distinguish AI-powered functionality from standard collaboration or formatting tools. By the end, you will be able to clearly define AI in this context and correctly identify at least two Confluence features that use AI.

In this module, you will move from recognizing AI features to applying them inside a real Confluence workflow. You will be introduced to Confluence pages as collaborative, living documents and practice building a structured page that can be updated over time. You will then use Confluence AI assistance to generate a summary paragraph and place it intentionally within the page so it supports team alignment and decision-making. By the end, you will produce an “AI Ideas” page that includes a clear structure, an AI-generated summary paragraph, and at least one organization element that makes the page easy to maintain.

You will connect an AI model to project content and configure automated insight generation to support ongoing visibility and decision-making.

You will evaluate AI-generated insights for accuracy and presentation quality, then refine parameters to improve reliability and usability.

You will design and implement a practical Confluence automation rule that eliminates manual status updates. The module focuses on rule logic, triggers, conditions, and safe deployment.

You will monitor automation outcomes, identify false triggers on archived pages, and refine rules using JQL for accuracy and efficiency.

This module establishes the foundation for automated governance reporting by walking you through Confluence REST API fundamentals and the /content endpoint. You will focus on authentic API usage, filtering by labels, and structuring responses for downstream dashboards.

This module focuses on evaluating and optimizing Confluence API scripts for real-world scale. You will analyze runtime behavior, identify inefficiencies, and apply pagination and rate-limit strategies to reduce API calls while preserving data integrity. The module emphasizes decision-making, tradeoffs, and documentation practices required for production-ready automation.

In this module, you will understand why automation matters and how Bash scripts replace fragile manual processes. You will build a secure, scheduled backup script that runs reliably without human intervention.

In this module, you will move beyond “the script works” to “the script works well.” You will evaluate automation performance using logs and execution data, identify bottlenecks, and refine scripts to significantly improve efficiency. You will begin practicing how to think like an automation owner reviewing, optimizing, and justifying improvements based on evidence.

This module equips you to use generative AI to improve how documentation and automation work is performed in real IT management contexts. You will learn not just how to use AI tools, but when and why to use them to achieve better outcomes. You will apply AI to real tasks such as drafting documentation, improving automation scripts, and optimizing workflows—while evaluating its impact on speed, quality, consistency, and effort reduction. You will also develop judgment in identifying when AI is appropriate, when manual work is preferable, and how to ensure outputs are accurate, reliable, and production-ready. By the end, you will be able to use AI as a practical productivity and decision-making tool, improving both efficiency and quality in your day-to-day work.

Automation enables teams to reduce manual effort, improve consistency, and scale workflows effectively. In this project, you will act as an IT Manager responsible for transforming a manual workflow into an automated system using Confluence and related tools. You will analyze an existing process, identify inefficiencies, and design an end-to-end automation pipeline that integrates rules, scripts, and optional AI components. You will implement trigger-based and scheduled automation, develop an API-based script, and document the system architecture and configuration. Beyond implementation, you will evaluate the effectiveness of your automation by comparing manual and automated workflows, identifying efficiency gains, and assessing system reliability. You will also justify your design decisions, considering trade-offs such as complexity, maintainability, and user experience. The final outcome is a fully documented automation system that demonstrates both technical capability and strategic decision-making, reflecting real-world expectations for IT management roles.