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⇱ Apply AI Techniques & Prescriptives | Coursera


Apply AI Techniques & Prescriptives

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Apply AI Techniques & Prescriptives

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Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

3 hours to complete
Flexible schedule
Learn at your own pace

Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

3 hours to complete
Flexible schedule
Learn at your own pace

What you'll learn

  • Successful AI integration combines multiple techniques aligned to business constraints, not single-model optimization.

  • Strong decisions balance accuracy and speed with interpretability and cost, guided by stakeholder priorities.

  • Optimization methods convert business constraints into measurable gains in profit and resource allocation.

  • Weighted scoring frameworks create transparent, defensible decisions that build stakeholder trust and alignment.

Details to know

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Recently updated!

March 2026

Assessments

6 assignmentsΒΉ

AI Graded see disclaimer
Taught in English

Build your subject-matter expertise

This course is part of the AI Techniques, Causal Inference & Business Optimization Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 3 modules in this course

Transform your analytical capabilities into competitive advantage with AI-powered decision intelligence.

This Short Course was created to help data analysts accomplish strategic business impact through advanced AI techniques and prescriptive analytics. By completing this course, you'll be able to build ensemble AI solutions that combine multiple methodologies, evaluate performance trade-offs across competing models, and implement optimization frameworks that drive measurable business outcomes. By the end of this course, you will be able to: Apply ensemble AI techniques to solve defined business problems with documented rationale Evaluate accuracy, latency, and interpretability trade-offs across multiple AI approaches Implement linear programming optimization for product mix and profit maximization Create weighted-scoring models for prescriptive scenario evaluation This course is unique because it bridges the gap between technical AI implementation and strategic business decision-making, providing hands-on experience with real-world optimization challenges. To be successful in this project, you should have a background in basic analytics, Python programming, and business problem-solving experience.

Learners will apply an ensemble of core, advanced, and generative AI techniques to solve a defined business decision problem while documenting model selection rationale.

What's included

2 videos1 reading1 assignment1 ungraded lab

2 videosβ€’Total 11 minutes
  • Implementing Ensemble AI Models Step-by-Stepβ€’5 minutes
  • Building Your First Ensemble AI Model with Pythonβ€’6 minutes
1 readingβ€’Total 10 minutes
  • Ensemble AI Techniques for Business Applicationsβ€’10 minutes
1 assignmentβ€’Total 6 minutes
  • Ensemble AI Techniques Assessmentβ€’6 minutes
1 ungraded labβ€’Total 20 minutes
  • Ensemble AI Model Development for Business Optimizationβ€’20 minutes

Learners will evaluate the performance trade-offs between accuracy, latency, and interpretability of at least three AI techniques on the same dataset and recommend the optimal choice.

What's included

1 video2 readings2 assignments

1 videoβ€’Total 3 minutes
  • Why Performance Trade-offs Matter in Business AI Decisionsβ€’3 minutes
2 readingsβ€’Total 17 minutes
  • Understanding AI Performance Trade-offs in Business Contextβ€’11 minutes
  • Podcast: Navigating AI Performance Trade-offs in Practiceβ€’6 minutes
2 assignmentsβ€’Total 25 minutes
  • Strategic AI Performance Trade-off Analysisβ€’18 minutes
  • AI Performance Trade-offs Evaluationβ€’7 minutes

Learners will apply linear programming optimization for product mix decisions and evaluate competing prescriptive scenarios using weighted-scoring models for stakeholder presentation.

What's included

2 videos3 assignments

2 videosβ€’Total 12 minutes
  • Linear Programming Fundamentals for Business Optimizationβ€’6 minutes
  • Implementing Linear Programming with Python for Product Mix Optimizationβ€’7 minutes
3 assignmentsβ€’Total 53 minutes
  • Comprehensive Prescriptive Optimization Implementationβ€’20 minutes
  • Prescriptive Optimization Assessmentβ€’8 minutes
  • Apply AI Techniques & Prescriptives - Course Assessmentβ€’25 minutes

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Instructor

454 Coursesβ€’58,950 learners

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Frequently asked questions

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Financial aid available,

ΒΉ Some assignments in this course are AI-graded. For these assignments, your data will be used in accordance with Coursera's Privacy Notice.