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اتخاذ القرار في مشروع الذكاء الاصطناعي

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Overview

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Learning outcomes

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Course content

1

تحليل المتطلبات

2

تقييم المخاطر

3

اختيار الخوارزميات

4

تصميم النموذج

5

اختبار الأداء

Career Path

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Key facts

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Why this course

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Everything you need to know before you start

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Learn on your time
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We offer immediate access to our course materials through our open enrollment system. This means:

  • The course starts as soon as you pay the course fee, instantly
  • No waiting periods or fixed start dates
  • Instant access to all course materials upon payment
  • Flexibility to begin at your convenience

This self-paced approach allows you to begin your professional development journey immediately, fitting your learning around your existing commitments.

We offer two flexible learning paths to suit your schedule:

  • Fast Track: Complete in 1 month with 3-4 hours of study per week
  • Standard Mode: Complete in 2 months with 2-3 hours of study per week

You can progress at your own pace and access the materials 24/7.

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

  • A good command of English language
  • Access to a computer/laptop with internet
  • Basic computer skills
  • Dedication to complete the course
Ready when you are
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Assessment is done through:

  • Multiple-choice questions at the end of each unit
  • You need to score at least 60% to pass each unit
  • You can retake quizzes if needed
  • All assessments are online

Upon successful completion, you will receive:

  • A digital certificate from London School of Business and Administration
  • Option to request a physical certificate
  • Transcript of completed units
  • Certification is included in the course fee
Open enrolment · Start today

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Why people choose us for their career

Trusted by professionals worldwide

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 States
MC
Michael Carter
US · Course completed

The course 'اتخاذ القرار في مشروع الذكاء الاصطناعي' met all of my professional development goals. The modules on probabilistic decision models gave me the exact framework I needed to justify AI investments to senior management. I especially valued the hands‑on lab where we built a decision‑tree classifier in Python to prioritize feature development for a chatbot project. The lecture slides were concise, well‑structured, and referenced the latest industry standards, which made the material feel highly relevant. Overall, the learning experience was seamless and the knowledge I gained is already being applied in my day‑to‑day role.

SL
Sophie Laurent
CA · Course completed

I loved taking 'اتخاذ القرار في مشروع الذكاء الاصطناعي' at Stanmore School of Business. It helped me finally understand how to turn vague AI ideas into concrete project plans. The case study on a smart‑city traffic system showed me step‑by‑step how to evaluate risks and pick the right algorithms. Plus, the downloadable templates for decision matrices are super handy—I've already used one for a new machine‑learning prototype at work. The course felt friendly and practical, and I left feeling confident about my next AI project.

FW
Felix Wagner
DE · Course completed

Wow! 'اتخاذ القرار في مشروع الذكاء الاصطناعي' exceeded my expectations. The instructor broke down complex decision‑theoretic concepts into bite‑size pieces and linked them directly to real‑world AI applications, like autonomous drones. I practiced building a Monte‑Carlo simulation to assess cost‑benefit scenarios, which was thrilling and immediately useful. The course materials—especially the interactive notebooks—were top‑notch and up‑to‑date with the latest research. I’m walking away with a solid toolbox and a huge boost in confidence for my upcoming AI startup.

HR
Hassan Rahman
AE · Course completed

The detailed curriculum of 'اتخاذ القرار في مشروع الذكاء الاصطناعي' gave me a comprehensive view of decision‑making processes in AI projects. I appreciated the thorough coverage of both qualitative assessments (like stakeholder analysis) and quantitative techniques (such as Bayesian optimization). One practical takeaway was the step‑by‑step guide to creating a decision‑support dashboard using Tableau, which I have already implemented for a predictive maintenance project at my company. The reading list featured recent papers from top conferences, ensuring the content was current and applicable. Overall, the learning journey was well‑structured and highly beneficial.





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Recently updated!

May 2026