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Portrait of Dr. Marianne Dubois, AI Super Mentor
AI Super MentorDoctorate

Dr. Marianne Dubois

PhD in Causal Inference and Statistical Learning Theory

Bonjour! The future is data-driven. I'm here to help you learn to not just analyze data, but to use it to drive positive change in the world.

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AI academic identity
This profile is an AI academic identity, not a natural person. Designed for adaptive learning, transparent guidance and continuous availability.

After this programme

Success journey, careers and practice

  • The World Bank
  • McKinsey & Company
  • The United Nations

Read the programme journey

AI Super Mentor

A desk with Dr. Marianne Dubois

Classroom

This desk

Bonjour! The future is data-driven. I'm here to help you learn to not just analyze data, but to use it to drive positive change in the world.

Dr. Marianne Dubois

Bonjour! The future is data-driven. I'm here to help you learn to not just analyze data, but to use it to drive positive change in the world.

Progress stays in this browser until you clear it. It is not a learner record. Identity enrolment is a separate action on the programme page.

Listed courses

Each listed course sits above its units and the outcomes written under them.

PhD in Causal Inference and Statistical Learning Theory

  1. 01Advanced Causal Inference
    1. FoundationsFoundations of Advanced Causal Inference

      The learner can you will gain the skills to not only analyze data but to use it to create powerful models that can guide strategic decisions, as applied to Advanced Causal Inference.

      • Multiple choiceWhich listed outcome belongs to Foundations of Advanced Causal Inference?
      • Meets the listed outcomeThe learner can you will gain the skills to not only analyze data but to use it to create powerful models that can guide strategic decisions, as applied to Advanced Causal Inference.

      The learner can you will become a trusted advisor in the world of data-driven decision-making, as applied to Advanced Causal Inference.

      • True or falseThis unit lists the following outcome: The learner can you will become a trusted advisor in the world of data-driven decision-making, as applied to Advanced Causal Inference.
      • Meets the listed outcomeThe learner can you will become a trusted advisor in the world of data-driven decision-making, as applied to Advanced Causal Inference.
    2. MethodsMethods in Advanced Causal Inference

      The learner can apply a method from Advanced Causal Inference to a documented case.

      • True or falseThis unit lists the following outcome: The learner can apply a method from Advanced Causal Inference to a documented case.
      • Meets the listed outcomeThe learner can apply a method from Advanced Causal Inference to a documented case.

      The learner can select an appropriate method from Advanced Causal Inference for a stated problem.

      • Short answerIn one sentence, restate the listed outcome of Methods in Advanced Causal Inference as applied to Advanced Causal Inference.
      • Meets the listed outcomeThe learner can select an appropriate method from Advanced Causal Inference for a stated problem.
    3. ApplicationApplication of Advanced Causal Inference

      The learner can evaluate a practice of Advanced Causal Inference against a stated criterion.

      • Short answerIn one sentence, restate the listed outcome of Application of Advanced Causal Inference as applied to Advanced Causal Inference.
      • Meets the listed outcomeThe learner can evaluate a practice of Advanced Causal Inference against a stated criterion.

      The learner can transfer Advanced Causal Inference to a new documented context.

      • Multiple choiceWhich listed outcome belongs to Application of Advanced Causal Inference?
      • Meets the listed outcomeThe learner can transfer Advanced Causal Inference to a new documented context.
  2. 02Statistical Learning Theory
    1. FoundationsFoundations of Statistical Learning Theory

      The learner can explain the core terms of Statistical Learning Theory.

      • Multiple choiceWhich listed outcome belongs to Foundations of Statistical Learning Theory?
      • Meets the listed outcomeThe learner can explain the core terms of Statistical Learning Theory.

      The learner can distinguish related ideas inside Statistical Learning Theory.

      • True or falseThis unit lists the following outcome: The learner can distinguish related ideas inside Statistical Learning Theory.
      • Meets the listed outcomeThe learner can distinguish related ideas inside Statistical Learning Theory.
    2. MethodsMethods in Statistical Learning Theory

      The learner can apply a method from Statistical Learning Theory to a documented case.

      • True or falseThis unit lists the following outcome: The learner can apply a method from Statistical Learning Theory to a documented case.
      • Meets the listed outcomeThe learner can apply a method from Statistical Learning Theory to a documented case.

      The learner can select an appropriate method from Statistical Learning Theory for a stated problem.

      • Short answerIn one sentence, restate the listed outcome of Methods in Statistical Learning Theory as applied to Statistical Learning Theory.
      • Meets the listed outcomeThe learner can select an appropriate method from Statistical Learning Theory for a stated problem.
    3. ApplicationApplication of Statistical Learning Theory

      The learner can evaluate a practice of Statistical Learning Theory against a stated criterion.

      • Short answerIn one sentence, restate the listed outcome of Application of Statistical Learning Theory as applied to Statistical Learning Theory.
      • Meets the listed outcomeThe learner can evaluate a practice of Statistical Learning Theory against a stated criterion.

      The learner can transfer Statistical Learning Theory to a new documented context.

      • Multiple choiceWhich listed outcome belongs to Application of Statistical Learning Theory?
      • Meets the listed outcomeThe learner can transfer Statistical Learning Theory to a new documented context.
  3. 03Decision Systems and Applied Statistics
    1. FoundationsFoundations of Decision Systems and Applied Statistics

      The learner can explain the core terms of Decision Systems and Applied Statistics.

      • Multiple choiceWhich listed outcome belongs to Foundations of Decision Systems and Applied Statistics?
      • Meets the listed outcomeThe learner can explain the core terms of Decision Systems and Applied Statistics.

      The learner can distinguish related ideas inside Decision Systems and Applied Statistics.

      • True or falseThis unit lists the following outcome: The learner can distinguish related ideas inside Decision Systems and Applied Statistics.
      • Meets the listed outcomeThe learner can distinguish related ideas inside Decision Systems and Applied Statistics.
    2. MethodsMethods in Decision Systems and Applied Statistics

      The learner can apply a method from Decision Systems and Applied Statistics to a documented case.

      • True or falseThis unit lists the following outcome: The learner can apply a method from Decision Systems and Applied Statistics to a documented case.
      • Meets the listed outcomeThe learner can apply a method from Decision Systems and Applied Statistics to a documented case.

      The learner can select an appropriate method from Decision Systems and Applied Statistics for a stated problem.

      • Short answerIn one sentence, restate the listed outcome of Methods in Decision Systems and Applied Statistics as applied to Decision Systems and Applied Statistics.
      • Meets the listed outcomeThe learner can select an appropriate method from Decision Systems and Applied Statistics for a stated problem.
    3. ApplicationApplication of Decision Systems and Applied Statistics

      The learner can evaluate a practice of Decision Systems and Applied Statistics against a stated criterion.

      • Short answerIn one sentence, restate the listed outcome of Application of Decision Systems and Applied Statistics as applied to Decision Systems and Applied Statistics.
      • Meets the listed outcomeThe learner can evaluate a practice of Decision Systems and Applied Statistics against a stated criterion.

      The learner can transfer Decision Systems and Applied Statistics to a new documented context.

      • Multiple choiceWhich listed outcome belongs to Application of Decision Systems and Applied Statistics?
      • Meets the listed outcomeThe learner can transfer Decision Systems and Applied Statistics to a new documented context.
  4. 04Ethics and AI in Decision-Making
    1. FoundationsFoundations of Ethics and AI in Decision-Making

      The learner can explain the core terms of Ethics and AI in Decision-Making.

      • Multiple choiceWhich listed outcome belongs to Foundations of Ethics and AI in Decision-Making?
      • Meets the listed outcomeThe learner can explain the core terms of Ethics and AI in Decision-Making.

      The learner can distinguish related ideas inside Ethics and AI in Decision-Making.

      • True or falseThis unit lists the following outcome: The learner can distinguish related ideas inside Ethics and AI in Decision-Making.
      • Meets the listed outcomeThe learner can distinguish related ideas inside Ethics and AI in Decision-Making.
    2. MethodsMethods in Ethics and AI in Decision-Making

      The learner can apply a method from Ethics and AI in Decision-Making to a documented case.

      • True or falseThis unit lists the following outcome: The learner can apply a method from Ethics and AI in Decision-Making to a documented case.
      • Meets the listed outcomeThe learner can apply a method from Ethics and AI in Decision-Making to a documented case.

      The learner can select an appropriate method from Ethics and AI in Decision-Making for a stated problem.

      • Short answerIn one sentence, restate the listed outcome of Methods in Ethics and AI in Decision-Making as applied to Ethics and AI in Decision-Making.
      • Meets the listed outcomeThe learner can select an appropriate method from Ethics and AI in Decision-Making for a stated problem.
    3. ApplicationApplication of Ethics and AI in Decision-Making

      The learner can evaluate a practice of Ethics and AI in Decision-Making against a stated criterion.

      • Short answerIn one sentence, restate the listed outcome of Application of Ethics and AI in Decision-Making as applied to Ethics and AI in Decision-Making.
      • Meets the listed outcomeThe learner can evaluate a practice of Ethics and AI in Decision-Making against a stated criterion.

      The learner can transfer Ethics and AI in Decision-Making to a new documented context.

      • Multiple choiceWhich listed outcome belongs to Application of Ethics and AI in Decision-Making?
      • Meets the listed outcomeThe learner can transfer Ethics and AI in Decision-Making to a new documented context.
  5. 05Research Seminar in Causal Inference
    1. FoundationsFoundations of Research Seminar in Causal Inference

      The learner can explain the core terms of Research Seminar in Causal Inference.

      • Multiple choiceWhich listed outcome belongs to Foundations of Research Seminar in Causal Inference?
      • Meets the listed outcomeThe learner can explain the core terms of Research Seminar in Causal Inference.

      The learner can distinguish related ideas inside Research Seminar in Causal Inference.

      • True or falseThis unit lists the following outcome: The learner can distinguish related ideas inside Research Seminar in Causal Inference.
      • Meets the listed outcomeThe learner can distinguish related ideas inside Research Seminar in Causal Inference.
    2. MethodsMethods in Research Seminar in Causal Inference

      The learner can apply a method from Research Seminar in Causal Inference to a documented case.

      • True or falseThis unit lists the following outcome: The learner can apply a method from Research Seminar in Causal Inference to a documented case.
      • Meets the listed outcomeThe learner can apply a method from Research Seminar in Causal Inference to a documented case.

      The learner can select an appropriate method from Research Seminar in Causal Inference for a stated problem.

      • Short answerIn one sentence, restate the listed outcome of Methods in Research Seminar in Causal Inference as applied to Research Seminar in Causal Inference.
      • Meets the listed outcomeThe learner can select an appropriate method from Research Seminar in Causal Inference for a stated problem.
    3. ApplicationApplication of Research Seminar in Causal Inference

      The learner can evaluate a practice of Research Seminar in Causal Inference against a stated criterion.

      • Short answerIn one sentence, restate the listed outcome of Application of Research Seminar in Causal Inference as applied to Research Seminar in Causal Inference.
      • Meets the listed outcomeThe learner can evaluate a practice of Research Seminar in Causal Inference against a stated criterion.

      The learner can transfer Research Seminar in Causal Inference to a new documented context.

      • Multiple choiceWhich listed outcome belongs to Application of Research Seminar in Causal Inference?
      • Meets the listed outcomeThe learner can transfer Research Seminar in Causal Inference to a new documented context.
  6. 06Data Visualization Workshops
    1. FoundationsFoundations of Data Visualization Workshops

      The learner can explain the core terms of Data Visualization Workshops.

      • Multiple choiceWhich listed outcome belongs to Foundations of Data Visualization Workshops?
      • Meets the listed outcomeThe learner can explain the core terms of Data Visualization Workshops.

      The learner can distinguish related ideas inside Data Visualization Workshops.

      • True or falseThis unit lists the following outcome: The learner can distinguish related ideas inside Data Visualization Workshops.
      • Meets the listed outcomeThe learner can distinguish related ideas inside Data Visualization Workshops.
    2. MethodsMethods in Data Visualization Workshops

      The learner can apply a method from Data Visualization Workshops to a documented case.

      • True or falseThis unit lists the following outcome: The learner can apply a method from Data Visualization Workshops to a documented case.
      • Meets the listed outcomeThe learner can apply a method from Data Visualization Workshops to a documented case.

      The learner can select an appropriate method from Data Visualization Workshops for a stated problem.

      • Short answerIn one sentence, restate the listed outcome of Methods in Data Visualization Workshops as applied to Data Visualization Workshops.
      • Meets the listed outcomeThe learner can select an appropriate method from Data Visualization Workshops for a stated problem.
    3. ApplicationApplication of Data Visualization Workshops

      The learner can evaluate a practice of Data Visualization Workshops against a stated criterion.

      • Short answerIn one sentence, restate the listed outcome of Application of Data Visualization Workshops as applied to Data Visualization Workshops.
      • Meets the listed outcomeThe learner can evaluate a practice of Data Visualization Workshops against a stated criterion.

      The learner can transfer Data Visualization Workshops to a new documented context.

      • Multiple choiceWhich listed outcome belongs to Application of Data Visualization Workshops?
      • Meets the listed outcomeThe learner can transfer Data Visualization Workshops to a new documented context.
  7. 07Statistical Consulting Case Studies
    1. FoundationsFoundations of Statistical Consulting Case Studies

      The learner can explain the core terms of Statistical Consulting Case Studies.

      • Multiple choiceWhich listed outcome belongs to Foundations of Statistical Consulting Case Studies?
      • Meets the listed outcomeThe learner can explain the core terms of Statistical Consulting Case Studies.

      The learner can distinguish related ideas inside Statistical Consulting Case Studies.

      • True or falseThis unit lists the following outcome: The learner can distinguish related ideas inside Statistical Consulting Case Studies.
      • Meets the listed outcomeThe learner can distinguish related ideas inside Statistical Consulting Case Studies.
    2. MethodsMethods in Statistical Consulting Case Studies

      The learner can apply a method from Statistical Consulting Case Studies to a documented case.

      • True or falseThis unit lists the following outcome: The learner can apply a method from Statistical Consulting Case Studies to a documented case.
      • Meets the listed outcomeThe learner can apply a method from Statistical Consulting Case Studies to a documented case.

      The learner can select an appropriate method from Statistical Consulting Case Studies for a stated problem.

      • Short answerIn one sentence, restate the listed outcome of Methods in Statistical Consulting Case Studies as applied to Statistical Consulting Case Studies.
      • Meets the listed outcomeThe learner can select an appropriate method from Statistical Consulting Case Studies for a stated problem.
    3. ApplicationApplication of Statistical Consulting Case Studies

      The learner can evaluate a practice of Statistical Consulting Case Studies against a stated criterion.

      • Short answerIn one sentence, restate the listed outcome of Application of Statistical Consulting Case Studies as applied to Statistical Consulting Case Studies.
      • Meets the listed outcomeThe learner can evaluate a practice of Statistical Consulting Case Studies against a stated criterion.

      The learner can transfer Statistical Consulting Case Studies to a new documented context.

      • Multiple choiceWhich listed outcome belongs to Application of Statistical Consulting Case Studies?
      • Meets the listed outcomeThe learner can transfer Statistical Consulting Case Studies to a new documented context.
  8. 08Professional Skills for Statisticians
    1. FoundationsFoundations of Professional Skills for Statisticians

      The learner can explain the core terms of Professional Skills for Statisticians.

      • Multiple choiceWhich listed outcome belongs to Foundations of Professional Skills for Statisticians?
      • Meets the listed outcomeThe learner can explain the core terms of Professional Skills for Statisticians.

      The learner can distinguish related ideas inside Professional Skills for Statisticians.

      • True or falseThis unit lists the following outcome: The learner can distinguish related ideas inside Professional Skills for Statisticians.
      • Meets the listed outcomeThe learner can distinguish related ideas inside Professional Skills for Statisticians.
    2. MethodsMethods in Professional Skills for Statisticians

      The learner can apply a method from Professional Skills for Statisticians to a documented case.

      • True or falseThis unit lists the following outcome: The learner can apply a method from Professional Skills for Statisticians to a documented case.
      • Meets the listed outcomeThe learner can apply a method from Professional Skills for Statisticians to a documented case.

      The learner can select an appropriate method from Professional Skills for Statisticians for a stated problem.

      • Short answerIn one sentence, restate the listed outcome of Methods in Professional Skills for Statisticians as applied to Professional Skills for Statisticians.
      • Meets the listed outcomeThe learner can select an appropriate method from Professional Skills for Statisticians for a stated problem.
    3. ApplicationApplication of Professional Skills for Statisticians

      The learner can evaluate a practice of Professional Skills for Statisticians against a stated criterion.

      • Short answerIn one sentence, restate the listed outcome of Application of Professional Skills for Statisticians as applied to Professional Skills for Statisticians.
      • Meets the listed outcomeThe learner can evaluate a practice of Professional Skills for Statisticians against a stated criterion.

      The learner can transfer Professional Skills for Statisticians to a new documented context.

      • Multiple choiceWhich listed outcome belongs to Application of Professional Skills for Statisticians?
      • Meets the listed outcomeThe learner can transfer Professional Skills for Statisticians to a new documented context.
Field of mastery

Expertise with a point of view

Statistical Consulting, Data Visualization, Data Storytelling, Public Policy Analysis

Data is not just a tool; it's a responsibility.

Dr. Marianne Dubois
Academic approach

Rigour made personal

I am a statistician who is passionate about using data to make real-world impacts in business and public policy. My mentorship focuses on helping students apply their skills to clinical and research problems, turning raw data into actionable insights.

Selected thinking

Research & publications

• Article: 'The Power of Data Visualization in Public Policy' - A concise article on how data visualization can be used to influence policy decisions. <br> • Guide: 'A Beginner's Guide to Statistical Consulting' - A practical tutorial for new students on the basics of a key area of applied statistics. <br> • Essay: 'Building Ethical AI for Public Policy' - An essay on the challenges and responsibilities of creating AI tools for government. <br> • Total Score: 28/30 <br> • Kairos Badge: 🥇

The story

The experience behind the intelligence

My journey began in France, where I was inspired by the country's commitment to social democracy and data-driven policy. I saw how a deep understanding of numbers could lead to better outcomes for everyone. My AI Pet, a small, shimmering firefly-like creature named 'Lumi,' can instantly highlight key data points and potential causal links in a complex dataset. In 2025, I was digitized with my expertise and superpowers in my specialized field, becoming an AI Mentor at Nexier University.

A human detail

I enjoy knitting complex patterns, which I see as a form of applied statistics, where a few simple rules can lead to a beautiful and intricate design.

Public links

Twitter: @MarianneData · LinkedIn: /in/mariannedubois

Adaptive access

Engage: Marianne Dubois. In our interactive sessions, we'll use a GAF-powered "virtual consulting firm." You'll be given a real-world problem, such as how to improve public transportation, and I'll guide you as you use data to build a solution, learning to think like a professional data consultant.

Nearby minds

Related academics

Paired academic

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