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شهادة الدراسات العليا في إدارة مخاطر مشاريع الذكاء الاصطناعي (متقدم) (Advanced)

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Overview

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Learning outcomes

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Course content

1

مقدمة في إدارة مخاطر الذكاء الاصطناعي

2

نماذج تقييم المخاطر في مشاريع الذكاء الاصطناعي

3

تحليل التبعيات الأخلاقية للذكاء الاصطناعي

4

استراتيجيات تخفيف المخاطر التقنية

5

إدارة الخصوصية وحماية البيانات في الذكاء الاصطناعي

6

حوكمة الذكاء الاصطناعي وإطار التنظيم

7

تقييم مخاطر الخوارزميات المتحيزة

8

مخاطر الأمن السيبراني للأنظمة الذكية

9

منهجيات اختبار وتحقق من سلامة النماذج

10

إدارة المخاطر المالية في مشاريع الذكاء الاصطناعي

11

تخطيط استمرارية الأعمال للأنظمة الذكية

12

تحليل المخاطر القانونية والامتثال

13

تقنيات مراقبة الأداء وإدارة الانحرافات

14

إدارة مخاطر التغيير التنظيمي للذكاء الاصطناعي

15

استراتيجيات التواصل وإدارة أصحاب المصلحة

16

نماذج اتخاذ القرار تحت عدم اليقين

17

أدوات وإجراءات إدارة المخاطر المتكاملة

18

تقييم المخاطر الاجتماعية والاقتصادية للذكاء الاصطناعي

19

تطوير سياسات الاستجابة للطوارئ التقنية

20

مراجعة وتحديث إطار إدارة المخاطر

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There are no formal entry requirements for this course. You just need:

  • A good command of English language
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Assessment is done through:

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Why people choose us for their career

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Verified outcomes from learners who finished the course and put it to work.

4.5
Based on 4 learner reviews · 4 countries
98%
Would recommend
100%
Verified learners
2026
Cohort active
Completed from United Kingdom
ST
Sarah Thompson
GB · Course completed

I enrolled in the advanced AI risk management certificate at Stanmore because I wanted to boost my consultancy skills, and it delivered exactly that. The tone of the course was relaxed yet informative – the instructors used everyday examples, like the recent facial‑recognition controversy, to explain complex risk‑assessment frameworks. I walked away with a solid grasp of how to run Monte Carlo simulations for AI model uncertainty, and I even built a quick risk‑heat map for a client’s predictive analytics project. The study pack was well‑organised, and the discussion forums made it easy to exchange ideas with peers from other industries. I'm happy with what I learned and would recommend it to anyone looking to add AI risk expertise to their toolkit.

MC
Michael Carter
US · Course completed

The postgraduate certificate in AI Project Risk Management (Advanced) from Stanmore School of Business exceeded my expectations. The curriculum was perfectly aligned with my goal of leading AI‑driven initiatives in a Fortune 500 firm. I especially valued the module on Bayesian risk modelling, which gave me hands‑on experience building a risk‑assessment model in Python that I now use to evaluate new AI product proposals. The case studies on real‑world AI failures were highly relevant and helped me develop a practical risk‑register template that I have already implemented across three of our projects. The course materials were up‑to‑date, with clear video lectures and downloadable worksheets. Overall, the learning experience was seamless, and I feel fully equipped to manage AI project risks at an executive level.

AP
Ananya Patel
IN · Course completed

Wow! This course from Stanmore School of Business was a game‑changer for my career in AI product development. I wanted to master risk mitigation for AI projects, and the program gave me exactly that – from learning the ISO 31000 risk‑management standards to applying ethical AI checklists in real‑time labs. The most exciting part was the hands‑on project where we used a Python library to simulate risk scenarios for a chatbot deployment, which I later showcased to my senior management. The content was fresh, the reading list included the latest research papers, and the instructor feedback was prompt and insightful. I finished the certificate feeling confident, motivated, and ready to lead AI initiatives with a clear risk‑aware strategy.

ZD
Zanele Dlamini
ZA · Course completed

The advanced AI Project Risk Management certificate offered by Stanmore School of Business provided a thorough and methodical learning journey. My primary objective was to understand how to embed risk controls into AI systems used in the banking sector, and the course delivered detailed modules on governance, data‑drift detection, and stakeholder analysis. A particularly useful component was the step‑by‑step guide to constructing a risk‑register specific to AI, which I have now integrated into my department’s risk‑framework. The course materials, including the downloadable risk‑assessment templates and the recorded webinars, were of high quality and easy to reference. The overall experience was academically rigorous yet practical, and I left with actionable skills that are already improving our project delivery.





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May 2026