Managing Software Projects

Course Description

New and experienced project managers looking to modernize their software management practice must adapt to the rapidly evolving landscape of AI-driven development. This interactive course equips project managers with key planning elements, modern techniques, effective communication strategies, and practical applications for integrating artificial intelligence into software project management. Participants will explore the common causes of software project failure while being introduced to cutting-edge methodologies, principles, and practices—including AI-assisted risk prediction, automated progress tracking, and AI-driven resource allocation.

This course is ideal for those seeking to enhance their skills for delivering full-scope, rigorously tested software projects on time and within budget using both traditional and AI-augmented tools. Students are guided through core processes aligned with the Project Management Institute (PMI) standards while learning how emerging AI workflows impact modern project lifecycles.

Learning Outcomes

At the conclusion of the course, you should be able to

• Select appropriately among methodologies: Evaluate and choose between traditional and modern project management frameworks—including Agile, Critical Path, and AI-augmented predictive scheduling—based on project needs.
• Leverage AI in project planning: Apply AI-driven tools for dynamic estimation, risk forecasting, automated resource optimization, and team performance analytics.
• Align with PMI standards: Execute core project processes and governance structures in alignment with the Project Management Institute, incorporating modern AI integrations into standard frameworks.
• Diagnose project failures: Analyze the root causes of software project failure, including technical debt, misaligned requirements, and algorithmic bias or unpredictability in AI systems.
• Implement preventative control actions: Establish proactive monitoring and preventative strategies—combining human oversight with automated project telemetry—for ongoing and future software initiatives.

Skills needed Knowledge of software development fundamentals and the development lifecycle.

*This course may be applied to a certificate only if you are currently declared in a program.

Additional Information

AI* - This course incorporates AI tools by integrating practical understanding and ethical considerations across the entire project lifecycle. The goal is to prepare students to work effectively in AI-enabled environments and manage AI-driven projects.