In "Automate, Debug, and Optimize Jira Workflows," beginners will master Jira's no-code automation engine to boost team efficiency. This module teaches you to build automated rules that eliminate repetitive tasks. Crucially, you will learn to troubleshoot when things go wrong by analyzing execution logs to perform evidence-based debugging. You'll also learn to optimize performance by identifying bottlenecks and refining rules. Through hands-on labs simulating real job tasks, you will build a portfolio proving your ability to manage the full lifecycle of workflow automation, making your processes more efficient and reliable.

This module explores the integration of Generative AI into IT support workflows to enhance issue tracking and triage. You will learn core concepts—including prompt engineering, text summarization, and zero-shot classification—while prioritizing ethical guardrails like "human-in-the-loop" oversight.

Manual ticket triage is slow and error-prone. In this project, you will solve this by designing an AI-augmented classifier to automate issue categorization. You will build a complete triage flow, including a critical "human-in-the-loop" check to ensure accuracy for low-confidence predictions. A key part of your work will be to measure the model's performance using precision and recall. You will deliver a final, data-backed recommendation on whether the classifier is ready for production, demonstrating your ability to deploy AI tools safely and effectively to improve a team's efficiency and responsiveness.