Managing AI projects requires more than ambition; it requires precision in planning and evaluation. In this course, Learners will learn how to define clear, measurable milestones with exit criteria, map dependencies to uncover critical path risks, and evaluate milestone completion reports against scope, quality, and readiness standards. Through videos, readings, and hands-on practice, they’ll gain confidence in turning vague project goals into structured milestones that drive accountability. Learners will practice using tools like PERT charts to identify blockers, analyze real-world milestone conflicts such as GPU procurement delays, and work through case studies where they must decide whether to approve or reject milestone closure. By the end, learners will be able to create milestone schedules, anticipate risks, and make evidence-based go/no-go decisions that ensure AI projects stay on track and deliver results with quality.

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Empfohlene Erfahrung
Kompetenzen, die Sie erwerben
- Kategorie: Decision Making
- Kategorie: Project Management
- Kategorie: Project Schedules
- Kategorie: Dependency Analysis
- Kategorie: Project Performance
- Kategorie: Project Scoping
- Kategorie: Estimation
- Kategorie: Project Planning
- Kategorie: Project Controls
- Kategorie: Milestones (Project Management)
- Kategorie: Smart Goals
- Kategorie: Risk Management
- Kategorie: Verification And Validation
Wichtige Details

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Dezember 2025
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In diesem Kurs gibt es 1 Modul
Managing AI projects requires more than ambition; it requires precision in planning and evaluation. In this course, Learners will learn how to define clear, measurable milestones with exit criteria, map dependencies to uncover critical path risks, and evaluate milestone completion reports against scope, quality, and readiness standards. Through videos, readings, and hands-on practice, they’ll gain confidence in turning vague project goals into structured milestones that drive accountability. Learners will practice using tools like PERT charts to identify blockers, analyze real-world milestone conflicts such as GPU procurement delays, and work through case studies where they must decide whether to approve or reject milestone closure. By the end, learners will be able to create milestone schedules, anticipate risks, and make evidence-based go/no-go decisions that ensure AI projects stay on track and deliver results with quality.
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5 Videos3 Lektüren4 Aufgaben
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Status: Vorschau
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¹ Einige Aufgaben in diesem Kurs werden mit AI bewertet. Für diese Aufgaben werden Ihre Daten in Übereinstimmung mit Datenschutzhinweis von Courseraverwendet.




