Program facts
- Study fee
- Free
- subjects
- 5
- lessons
- 20
- Estimated time
- 14.5 hours
- Access period
- 60 days
- Study language
- Arabic and English
About the program
This diploma builds a structured foundation in decision-making and problem-solving without assuming advanced prior experience. It begins with problem definition, the desired state and information quality, then develops objectives, alternatives, criteria and trade-offs. It introduces simple probabilities, expected value and basic decision trees, and explains how heuristics such as availability, representativeness, anchoring and framing can influence judgment without treating them as diagnoses of people. It closes with small tests of critical assumptions, implementation monitoring and post-decision review.
Practical relevance
The process can be used for work and practical-life decisions: choosing among options, investigating a recurring problem, testing an assumption before full commitment, or reviewing a past decision. Learning cases are fictional and country-neutral and can be adapted without sharing confidential information.
Why this program
Practical difficulty rarely comes from lacking one tool. The harder task is moving from ambiguity to a decision that can be explained, tested and reviewed. The program therefore connects problem framing, evidence quality, alternatives, criteria, uncertainty, biases, small experiments and post-decision review in one coherent process.
Career relevance
These skills are useful in roles that compare alternatives, investigate problems or act on incomplete information, including management, supervision, projects, operations, product work and services. The diploma does not confer a regulated professional authority and does not replace domain expertise where specialized judgment is required.
What you will learn
- Frame a problem or decision by defining the desired state, scope and constraints.
- Distinguish symptoms from possible causes and verify causal hypotheses with appropriate evidence.
- Build objectives, criteria, alternatives and trade-offs, and test how sensitive a recommendation is.
- Use simple probabilities, expected value and basic decision trees without treating expected value as a guaranteed outcome.
- Recognize selected judgment biases and use practical practices to reduce their influence.
- Test critical assumptions on a small scale, then document, monitor and review the decision after outcomes appear.
Learning outcomes (10)
- Frame a problem or decision clearly by defining the desired state, scope, constraints and affected stakeholders.
- Distinguish symptoms from causal hypotheses and choose an appropriate way to gather evidence that helps verify possible causes.
- Evaluate information quality, assumptions and sources of uncertainty, and judge when additional information could change a decision.
- Define objectives, decision criteria and mandatory constraints in a way that supports transparent comparison.
- Generate meaningful alternatives and compare them using a decision matrix, trade-offs and simple sensitivity analysis.
- Interpret simple probabilities, build a simple decision tree and calculate expected value while distinguishing it from a guaranteed outcome.
- Recognize availability, representativeness, anchoring and framing as judgment tendencies and use practices that reduce their influence without diagnosing people.
- Design a proportionate small test for a critical assumption, with a hypothesis, decision criterion and clear boundaries before scaling.
- Document decision rationale, implement it and monitor it using indicators and decision points that support continuing, stopping, scaling or adapting.
- Conduct a post-decision review that separates what was knowable at decision time from the later outcome and captures transferable lessons for future decisions.
Who it is for
- Learners and professionals seeking a structured foundation in Decision-Making and Problem-Solving.
- People seeking applicable knowledge without requiring advanced prior experience.
Prerequisites
- No advanced experience is required. Learners need only basic comfort reading practical examples and performing simple probability and percentage calculations taught within the program.
What it does not offer
- Learners seeking to diagnose people psychologically from heuristics or biases.
- Situations requiring specialized legal, clinical or financial judgment instead of an appropriate domain expert.
Curriculum
- Subject 1 Open for free
Framing Problems and Decisions
Builds the foundation for defining what is actually being decided, what the problem is, and what information is available before choosing a tool or solution.
- Subject 2
Objectives, Alternatives and Criteria
Moves from clear objectives to alternatives, criteria and trade-offs that can be explained and tested for sensitivity.
- Subject 3
Uncertainty, Decision Trees and Biases
Introduces uncertainty, probability, expected value and simple decision trees while treating biases as judgment tendencies rather than diagnoses.
- Subject 4
Testing Solutions and Learning from Evidence
Focuses on reducing uncertainty through testable hypotheses, small experiments and pre-agreed decision criteria before broad implementation.
- Subject 5
Post-Decision Review and Integrated Practice
Integrates documentation, monitoring and post-decision review so lessons can be captured without judging the decision by outcome alone.
Subjects unlock in sequence as you progress.
Strengths
- A complete learning arc from framing a problem to post-decision review rather than a disconnected catalogue of tools.
- A balanced introduction to qualitative and simple quantitative reasoning: criteria and trade-offs alongside probability, expected value and basic decision trees.
- An explicit separation between decision-process quality and later outcome, reducing hindsight-based evaluation of choices.
- Clear separation between formative learning checks and credential-counting summative banks, with one independent summative per subject.
Evidence basis
The blueprint draws on primary and professional sources including U.S. Fish & Wildlife Service Structured Decision Making materials, NASA Decision Analysis guidance, ASQ problem-solving resources, original research on heuristics and framing, OpenStax for expected value, and GOV.UK Test and Learn guidance. References reflect only the material actually accessed and do not imply reading or reproducing unavailable source content.
Reference organizations
- U.S. Fish & Wildlife Service
- NASA
- ASQ
- Science / PubMed
- OpenStax
- UK Government
Frameworks used
- Structured Decision Making / PrOACT
- NASA Decision Analysis — NASA public HTML section 6.8
- Root Cause Analysis concepts
- Test and Learn — GOV.UK HTML guidance
Methodology
Concepts are organized into a foundational progression from framing and information quality to alternatives and criteria, uncertainty, testing and learning, then post-decision review. No single framework is presented as the only recipe for every situation.
How the route works
Short Diplomas are relatively comprehensive learning pathways that cover a major subject through five connected learning subjects and structured assessments, with a diploma transcript available with the credential.
Self-paced sequential study. Content unlocks progressively and each subject combines reading, examples, exercises, knowledge checks, and assessment.
- Build integrated knowledge in a major subject.
- Study through five clear, connected learning subjects.
- Complete a defined assessment for each subject.
- Receive a diploma transcript showing subjects and results when the credential is issued.
Assessment
Each Short Diploma contains five subjects, each with an approved assessment. A sixth final exam is not required when the five assessments adequately cover the learning outcomes.
Assessment attempts: 2 per assessment, 7 days apart
The pass mark is announced before the program is published.
Certificate
Successful completion makes the learner eligible for the Short Diploma certificate and Diploma Transcript under the credential policy.
Every certificate has a public verification code. Verify a certificate
Disclaimer: Training completion, not a university degree or professional licence.
Program questions
Do I need advanced prior experience?
No. The diploma is designed as a connected adult-learning foundation with progressive examples and applications. Work experience can help with transfer, but it is not required to begin.
Does the program teach one method for every problem?
No. It teaches a structured process for choosing an appropriate level of analysis and suitable tools for the decision, available information and uncertainty.
Is expected value the outcome that will definitely occur?
No. Expected value is a probability-weighted long-run average. It can support comparison under stated assumptions, but it does not guarantee the result of a single decision.
Does calling something a bias diagnose a person?
No. The program treats biases as documented tendencies in judgment and teaches process safeguards. It does not use them to make psychological diagnoses of individuals.
Are decision trees included?
Yes, at a foundational level: representing simple choices, chance events and outcomes, then calculating expected value where appropriate while keeping assumptions visible.
How does the program handle incomplete information?
It teaches you to expose assumptions and uncertainties, judge whether more information could change the choice, and use sensitivity analysis or a small test when proportionate.
How is learning assessed?
Short knowledge checks are linked to lessons, followed by one independent summative assessment per subject. The central passing threshold is not invented in this authoring file and remains governed by platform policy.