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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AI Project Milestones with Confidence
Dieser Kurs ist Teil von Spezialisierung für Managing AI Projects That Ship and Scale
Dozent: ansrsource instructors
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Empfohlene Erfahrung
Kompetenzen, die Sie erwerben
- Kategorie: Milestones (Project Management)
- Kategorie: Smart Goals
- Kategorie: Project Performance
- Kategorie: Project Controls
- Kategorie: Verification And Validation
- Kategorie: Project Schedules
- Kategorie: Project Scoping
- Kategorie: Risk Management
- Kategorie: Project Management
- Kategorie: Project Planning
- Kategorie: Dependency Analysis
- Kategorie: Decision Making
- Kategorie: Estimation
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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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Mehr von Leadership and Management entdecken
Status: VorschauJohns Hopkins University
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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.