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Implications of Artificial Intelligence on Project Management

The IIL Blog

By Eugene Bounds and Steve Ackert Recently, the buzzword artificial intelligence (AI) has been on everyone’s minds, not just in the tech world but across many industries, including project management. While some tools (e.g., While some tools (e.g., Weekly, new tools and capabilities are being introduced.

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In-Depth: The Evidence-Based Business Case For Agile

Scrum.org

This tool uses a validated and scale-based questionnaire to allow teams to diagnose and improve their process in an evidence-based way. So we went to Google Scholar and searched for review articles. 2010) reviewed 28 scientific studies that investigated how Scrum is associated with overall business outcomes. Cardozo et.

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Development Team Anti-Patterns

Scrum.org

Source : Scrum Guide 2017. . Check out the complete Scrum Guide 2017 list on the Development Team by downloading the Scrum Guide Reordered.). Finally, the term Development Team seems to limit the role to technical people, for example, software engineers. Read more on technical debt and Scrum.).

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Project Delivery through the Definition of Done

Project Pulse Journal

Due to their different approaches to project management, this definition varies significantly between Agile and Waterfall methodologies. Extreme Programming (XP) - The DoD includes passing all unit tests, code reviews, and integration tests. They should include specific performance metrics, testing requirements, and review processes.

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How to Become a Software Project Manager (Full Guide)

PM Basics

But you don’t have a relevant degree, experience, or technical background…. Below you’ll find a full guide on how to become a software PM. TL;DR: The steps to becoming a software project manager. Develop technical proficiency. Technical Skills of an IT Project Manager. Step #2: Improve Your Technical Awareness.

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Risk Management Resources

Herding Cats

Information about key project cost, (technical) performance, and schedule attributes is often uncertain or unknown until late in the program. Taxonomy-Based Risk Identification,” Marvin Carr, Suresh Konda, Ira Monarch, Carlo Ulrich, and Clay Walker, Technical Report, CMU/SEI-93-TR-6, Software Engineering Institute, June 1993.

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A Compendium of Risk Management Resources

Herding Cats

Let's start with a critical understanding of the purpose of managing risk on software development projects. Information about key project cost, (technical) performance and schedule attributes is often uncertain or unknown until late in the program. IEEE Transactions on Software Engineering , Vol. De Meyer, C.