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AI for Agile Delivery in Jira and Azure DevOps
Published 9/2026
Created by Ganesh Ravikumar
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 40 Lectures ( 4h 24m ) | Size: 1.2 GB
Practical AI for scrum masters, product owners and delivery leads - sprint planning, triage, metrics and reporting
What you'll learn
Decide which delivery problems in Jira and Azure DevOps are worth automating first, and which are not worth touching Write user stories and acceptance criteria that do not come back with questions after review Turn a vague bug report into a reproducible one, and split work items that are too big to estimate Clean a neglected backlog in an afternoon, including duplicates and near-duplicates Use AI in estimation without inheriting the bad habits buried in your own ticket history Generate a sprint goal and planning summary that a team will actually read and use Produce JQL and WIQL queries without learning either syntax properly Read flow metrics - cycle time, throughput, ageing work - and spot an AI narrative that is wrong Summarise a sprint three different ways for the team, the product owner and an executive Build automation rules in both tools with an AI step in the right place, not the wrong one Know what must never go into a prompt, and how licensing, admin controls and cost actually work Roll AI into a delivery team's week in thirty days without the team rejecting itRequirements
You should already run sprints or manage work in Jira or Azure DevOps - this is not an introduction to either tool Access to a board you can experiment on, ideally your own team's or a free personal project No coding required at all - there is no scripting in this courseDescription
This course contains the use of artificial intelligence.
AI is used to reframe the words, fixing spelling mistakes and grammatical mistakes and audio conversion.
Your backlog has four hundred items and nobody has read the bottom two hundred since last year.That is the actual problem, and it is not a tooling problem. Delivery teams do not struggle because Jira or Azure DevOps lacks features - both have more features than any team uses. They struggle because the work of keeping a board honest is tedious, repetitive and always the first thing dropped when a sprint gets tight. Stories get written in a hurry and come back with questions. Duplicates accumulate. The status report gets assembled on a Monday morning by somebody who should be doing something else.
That work is exactly what AI is good at, and it is not what most people try to use it for.This course covers where AI genuinely helps across the delivery cycle in both Jira and Azure DevOps: writing work items that do not bounce back, cleaning a neglected backlog, estimation and sprint planning, triage and routing, flow metrics, release notes, and the weekly status update. Both platforms are covered side by side in every section, because a great many delivery people have to work across both after a merger or a migration, and the differences matter more than the marketing suggests.
It also covers where AI misleads you, which most courses skip. A generated sprint summary will confidently smooth over the thing you most needed to escalate. An estimate produced from historical tickets inherits every bad habit in that history. A metrics narrative will find a trend in four data points. You will learn to spot each of those, because being wrong in front of your own team is expensive and it is how teams end up rejecting a tool that actually worked.This is a practical course for scrum masters, product owners, delivery and project managers, business analysts, PMO staff and engineering managers. It assumes you already run sprints in one of these tools. It does not assume you can code, and there is no scripting in it.
Every section ends with a hands-on exercise you run against your own board, so you finish with a cleaned backlog, three working automation rules, and a weekly update that takes ten minutes instead of a morning.This course is not affiliated with, endorsed by, or sponsored by Atlassian or Microsoft. AI features in both products change frequently, so the course teaches the judgement about when to use them and when not to, which outlasts any particular release.
Who this course is for
Scrum masters and agile coaches who spend too much of the sprint on board maintenance Product owners and business analysts who write work items and want fewer of them bouncing back Delivery and project managers who assemble status reports by hand every week PMO and portfolio staff who need consistent reporting across teams using different tools Engineering managers who have inherited both Jira and Azure DevOps after a merger or migrationHomepage
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