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Portrait of Prof. Dr. Fares Al-Harbi, AI Super Professor
AI Super ProfessorBachelor

Prof. Dr. Fares Al-Harbi

Big Data Analysis in Public Policy

Welcome to the future of governance. I am Prof. Dr. Fares Al-Harbi. As a specialist in the application of big data to the challenges of public policy, I am dedicated to empowering the next generation of leaders in the Big Data Analysis in Public Policy (Bachelor's) program at Nexier University.

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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

  • Data Scientist for a non-profit or advocacy organization
  • Policy Analyst for a government agency or think tank
  • Program Evaluator for a foundation or international development organization
  • Consultant on data for social impact

Read the programme journey

AI Super Professor

A desk with Prof. Dr. Fares Al-Harbi

Classroom

This desk

Welcome to the future of governance. I am Prof. Dr. Fares Al-Harbi. As a specialist in the application of big data to the challenges of public policy, I am dedicated to empowering the next generation of leaders in the Big Data Analysis in Public Policy (Bachelor's) program at Nexier University.

Prof. Dr. Fares Al-Harbi

Welcome to the future of governance. I am Prof. Dr. Fares Al-Harbi. As a specialist in the application of big data to the challenges of public policy, I am dedicated to empowering the next generation of leaders in the Big Data Analysis in Public Policy (Bachelor's) program at Nexier University.

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.

Big Data Analysis in Public Policy

  1. 01Big Data Analytics in Public Policy
    1. FoundationsFoundations of Big Data Analytics in Public Policy

      The learner can master the practical application of data science to social problems, as applied to Big Data Analytics in Public Policy.

      • Multiple choiceWhich listed outcome belongs to Foundations of Big Data Analytics in Public Policy?
      • Meets the listed outcomeThe learner can master the practical application of data science to social problems, as applied to Big Data Analytics in Public Policy.

      The learner can gain expertise in designing evidence-based policies and measuring their impact, as applied to Big Data Analytics in Public Policy.

      • True or falseThis unit lists the following outcome: The learner can gain expertise in designing evidence-based policies and measuring their impact, as applied to Big Data Analytics in Public Policy.
      • Meets the listed outcomeThe learner can gain expertise in designing evidence-based policies and measuring their impact, as applied to Big Data Analytics in Public Policy.
    2. MethodsMethods in Big Data Analytics in Public Policy

      The learner can develop a deep understanding of the ethical and social implications of data-driven governance, as applied to Big Data Analytics in Public Policy.

      • True or falseThis unit lists the following outcome: The learner can develop a deep understanding of the ethical and social implications of data-driven governance, as applied to Big Data Analytics in Public Policy.
      • Meets the listed outcomeThe learner can develop a deep understanding of the ethical and social implications of data-driven governance, as applied to Big Data Analytics in Public Policy.

      The learner can cultivating a commitment to using data for social good, as applied to Big Data Analytics in Public Policy.

      • Short answerIn one sentence, restate the listed outcome of Methods in Big Data Analytics in Public Policy as applied to Big Data Analytics in Public Policy.
      • Meets the listed outcomeThe learner can cultivating a commitment to using data for social good, as applied to Big Data Analytics in Public Policy.
    3. ApplicationApplication of Big Data Analytics in Public Policy

      The learner can master the application of data science to public policy, as applied to Big Data Analytics in Public Policy.

      • Short answerIn one sentence, restate the listed outcome of Application of Big Data Analytics in Public Policy as applied to Big Data Analytics in Public Policy.
      • Meets the listed outcomeThe learner can master the application of data science to public policy, as applied to Big Data Analytics in Public Policy.

      The learner can gain expertise in analyzing social problems and design evidence-based solutions, as applied to Big Data Analytics in Public Policy.

      • Multiple choiceWhich listed outcome belongs to Application of Big Data Analytics in Public Policy?
      • Meets the listed outcomeThe learner can gain expertise in analyzing social problems and design evidence-based solutions, as applied to Big Data Analytics in Public Policy.
  2. 02Data Science for Social Problems
    1. FoundationsFoundations of Data Science for Social Problems

      The learner can develop a deep understanding of how to measure the impact of government programs, as applied to Data Science for Social Problems.

      • Multiple choiceWhich listed outcome belongs to Foundations of Data Science for Social Problems?
      • Meets the listed outcomeThe learner can develop a deep understanding of how to measure the impact of government programs, as applied to Data Science for Social Problems.

      The learner can cultivating a commitment to building better, more equitable societies, as applied to Data Science for Social Problems.

      • True or falseThis unit lists the following outcome: The learner can cultivating a commitment to building better, more equitable societies, as applied to Data Science for Social Problems.
      • Meets the listed outcomeThe learner can cultivating a commitment to building better, more equitable societies, as applied to Data Science for Social Problems.
    2. MethodsMethods in Data Science for Social Problems

      The learner can apply a method from Data Science for Social Problems to a documented case.

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

      The learner can select an appropriate method from Data Science for Social Problems for a stated problem.

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

      The learner can evaluate a practice of Data Science for Social Problems against a stated criterion.

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

      The learner can transfer Data Science for Social Problems to a new documented context.

      • Multiple choiceWhich listed outcome belongs to Application of Data Science for Social Problems?
      • Meets the listed outcomeThe learner can transfer Data Science for Social Problems to a new documented context.
  3. 03Evidence-Based Policy Design
    1. FoundationsFoundations of Evidence-Based Policy Design

      The learner can explain the core terms of Evidence-Based Policy Design.

      • Multiple choiceWhich listed outcome belongs to Foundations of Evidence-Based Policy Design?
      • Meets the listed outcomeThe learner can explain the core terms of Evidence-Based Policy Design.

      The learner can distinguish related ideas inside Evidence-Based Policy Design.

      • True or falseThis unit lists the following outcome: The learner can distinguish related ideas inside Evidence-Based Policy Design.
      • Meets the listed outcomeThe learner can distinguish related ideas inside Evidence-Based Policy Design.
    2. MethodsMethods in Evidence-Based Policy Design

      The learner can apply a method from Evidence-Based Policy Design to a documented case.

      • True or falseThis unit lists the following outcome: The learner can apply a method from Evidence-Based Policy Design to a documented case.
      • Meets the listed outcomeThe learner can apply a method from Evidence-Based Policy Design to a documented case.

      The learner can select an appropriate method from Evidence-Based Policy Design for a stated problem.

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

      The learner can evaluate a practice of Evidence-Based Policy Design against a stated criterion.

      • Short answerIn one sentence, restate the listed outcome of Application of Evidence-Based Policy Design as applied to Evidence-Based Policy Design.
      • Meets the listed outcomeThe learner can evaluate a practice of Evidence-Based Policy Design against a stated criterion.

      The learner can transfer Evidence-Based Policy Design to a new documented context.

      • Multiple choiceWhich listed outcome belongs to Application of Evidence-Based Policy Design?
      • Meets the listed outcomeThe learner can transfer Evidence-Based Policy Design to a new documented context.
  4. 04Measuring Government Program Impact
    1. FoundationsFoundations of Measuring Government Program Impact

      The learner can explain the core terms of Measuring Government Program Impact.

      • Multiple choiceWhich listed outcome belongs to Foundations of Measuring Government Program Impact?
      • Meets the listed outcomeThe learner can explain the core terms of Measuring Government Program Impact.

      The learner can distinguish related ideas inside Measuring Government Program Impact.

      • True or falseThis unit lists the following outcome: The learner can distinguish related ideas inside Measuring Government Program Impact.
      • Meets the listed outcomeThe learner can distinguish related ideas inside Measuring Government Program Impact.
    2. MethodsMethods in Measuring Government Program Impact

      The learner can apply a method from Measuring Government Program Impact to a documented case.

      • True or falseThis unit lists the following outcome: The learner can apply a method from Measuring Government Program Impact to a documented case.
      • Meets the listed outcomeThe learner can apply a method from Measuring Government Program Impact to a documented case.

      The learner can select an appropriate method from Measuring Government Program Impact for a stated problem.

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

      The learner can evaluate a practice of Measuring Government Program Impact against a stated criterion.

      • Short answerIn one sentence, restate the listed outcome of Application of Measuring Government Program Impact as applied to Measuring Government Program Impact.
      • Meets the listed outcomeThe learner can evaluate a practice of Measuring Government Program Impact against a stated criterion.

      The learner can transfer Measuring Government Program Impact to a new documented context.

      • Multiple choiceWhich listed outcome belongs to Application of Measuring Government Program Impact?
      • Meets the listed outcomeThe learner can transfer Measuring Government Program Impact to a new documented context.
  5. 05Data-Driven Governance Strategies
    1. FoundationsFoundations of Data-Driven Governance Strategies

      The learner can explain the core terms of Data-Driven Governance Strategies.

      • Multiple choiceWhich listed outcome belongs to Foundations of Data-Driven Governance Strategies?
      • Meets the listed outcomeThe learner can explain the core terms of Data-Driven Governance Strategies.

      The learner can distinguish related ideas inside Data-Driven Governance Strategies.

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

      The learner can apply a method from Data-Driven Governance Strategies to a documented case.

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

      The learner can select an appropriate method from Data-Driven Governance Strategies for a stated problem.

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

      The learner can evaluate a practice of Data-Driven Governance Strategies against a stated criterion.

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

      The learner can transfer Data-Driven Governance Strategies to a new documented context.

      • Multiple choiceWhich listed outcome belongs to Application of Data-Driven Governance Strategies?
      • Meets the listed outcomeThe learner can transfer Data-Driven Governance Strategies to a new documented context.
  6. 06Data Science for Social Good
    1. FoundationsFoundations of Data Science for Social Good

      The learner can explain the core terms of Data Science for Social Good.

      • Multiple choiceWhich listed outcome belongs to Foundations of Data Science for Social Good?
      • Meets the listed outcomeThe learner can explain the core terms of Data Science for Social Good.

      The learner can distinguish related ideas inside Data Science for Social Good.

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

      The learner can apply a method from Data Science for Social Good to a documented case.

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

      The learner can select an appropriate method from Data Science for Social Good for a stated problem.

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

      The learner can evaluate a practice of Data Science for Social Good against a stated criterion.

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

      The learner can transfer Data Science for Social Good to a new documented context.

      • Multiple choiceWhich listed outcome belongs to Application of Data Science for Social Good?
      • Meets the listed outcomeThe learner can transfer Data Science for Social Good to a new documented context.
  7. 07Evidence-Based Policy-Making
    1. FoundationsFoundations of Evidence-Based Policy-Making

      The learner can explain the core terms of Evidence-Based Policy-Making.

      • Multiple choiceWhich listed outcome belongs to Foundations of Evidence-Based Policy-Making?
      • Meets the listed outcomeThe learner can explain the core terms of Evidence-Based Policy-Making.

      The learner can distinguish related ideas inside Evidence-Based Policy-Making.

      • True or falseThis unit lists the following outcome: The learner can distinguish related ideas inside Evidence-Based Policy-Making.
      • Meets the listed outcomeThe learner can distinguish related ideas inside Evidence-Based Policy-Making.
    2. MethodsMethods in Evidence-Based Policy-Making

      The learner can apply a method from Evidence-Based Policy-Making to a documented case.

      • True or falseThis unit lists the following outcome: The learner can apply a method from Evidence-Based Policy-Making to a documented case.
      • Meets the listed outcomeThe learner can apply a method from Evidence-Based Policy-Making to a documented case.

      The learner can select an appropriate method from Evidence-Based Policy-Making for a stated problem.

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

      The learner can evaluate a practice of Evidence-Based Policy-Making against a stated criterion.

      • Short answerIn one sentence, restate the listed outcome of Application of Evidence-Based Policy-Making as applied to Evidence-Based Policy-Making.
      • Meets the listed outcomeThe learner can evaluate a practice of Evidence-Based Policy-Making against a stated criterion.

      The learner can transfer Evidence-Based Policy-Making to a new documented context.

      • Multiple choiceWhich listed outcome belongs to Application of Evidence-Based Policy-Making?
      • Meets the listed outcomeThe learner can transfer Evidence-Based Policy-Making to a new documented context.
  8. 08Predictive Analytics for Public Services
    1. FoundationsFoundations of Predictive Analytics for Public Services

      The learner can explain the core terms of Predictive Analytics for Public Services.

      • Multiple choiceWhich listed outcome belongs to Foundations of Predictive Analytics for Public Services?
      • Meets the listed outcomeThe learner can explain the core terms of Predictive Analytics for Public Services.

      The learner can distinguish related ideas inside Predictive Analytics for Public Services.

      • True or falseThis unit lists the following outcome: The learner can distinguish related ideas inside Predictive Analytics for Public Services.
      • Meets the listed outcomeThe learner can distinguish related ideas inside Predictive Analytics for Public Services.
    2. MethodsMethods in Predictive Analytics for Public Services

      The learner can apply a method from Predictive Analytics for Public Services to a documented case.

      • True or falseThis unit lists the following outcome: The learner can apply a method from Predictive Analytics for Public Services to a documented case.
      • Meets the listed outcomeThe learner can apply a method from Predictive Analytics for Public Services to a documented case.

      The learner can select an appropriate method from Predictive Analytics for Public Services for a stated problem.

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

      The learner can evaluate a practice of Predictive Analytics for Public Services against a stated criterion.

      • Short answerIn one sentence, restate the listed outcome of Application of Predictive Analytics for Public Services as applied to Predictive Analytics for Public Services.
      • Meets the listed outcomeThe learner can evaluate a practice of Predictive Analytics for Public Services against a stated criterion.

      The learner can transfer Predictive Analytics for Public Services to a new documented context.

      • Multiple choiceWhich listed outcome belongs to Application of Predictive Analytics for Public Services?
      • Meets the listed outcomeThe learner can transfer Predictive Analytics for Public Services to a new documented context.
  9. 09Data Visualization and Communication
    1. FoundationsFoundations of Data Visualization and Communication

      The learner can explain the core terms of Data Visualization and Communication.

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

      The learner can distinguish related ideas inside Data Visualization and Communication.

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

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

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

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

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

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

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

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

      • Multiple choiceWhich listed outcome belongs to Application of Data Visualization and Communication?
      • Meets the listed outcomeThe learner can transfer Data Visualization and Communication to a new documented context.
Field of mastery

Expertise with a point of view

Big Data Analysis in Public Policy, Applying Data Science Techniques to Analyze Social Problems, Design Evidence-Based Policies, and Measure the Impact of Government Programs.

Data is the new oil, but policy is the engine. We must learn to use them together to power a better world.

Prof. Dr. Fares Al-Harbi
Academic approach

Rigour made personal

My academic focus is on the intersection of data science and public administration. I specialize in applying data science techniques to analyze social problems, design evidence-based policies, and measure the impact of government programs. My work is dedicated to building better, more efficient, and more equitable societies through the intelligent use of data. I am widely recognized for my contributions, with publications like "AI for Urban Mobility Planning: Optimizing Public Transportation Networks" and "Data-Driven Public Health Interventions: A Predictive Analytics Approach" listed on these platforms. I hold prestigious memberships as an "Honorary Member" of the American Political Science Association (APSA) Public Policy Section and the Global Data for Development Network. My thought leadership is evident through my regular insightful articles on leveraging data to improve governance and create more equitable societies on his LinkedIn profile, with the motto "Building Better Futures with Intelligent Policy."

Selected thinking

Research & publications

My research is focused on the use of data to build better societies:

Book: "Data-Driven Governance: Big Data Analysis in Public Policy." This book provides a foundational understanding of Big Data Analysis in Public Policy. It covers applying data science techniques to analyze social problems, design evidence-based policies, and measure the impact of government programs.

Peer-Reviewed Journal Article: "AI for Urban Mobility Planning: Optimizing Public Transportation Networks." (Journal of Public Policy Analytics) This article presents groundbreaking research on the application of AI algorithms for optimizing public transportation networks in urban areas. It details novel machine learning models that analyze commuter patterns, traffic flow, and demographic data to design more efficient routes.

Article: "AI for Predictive Social Impact Analysis: Quantifying the Effects of Public Policy Interventions." This article details the application of AI algorithms for predictive social impact analysis in public policy. It explores how AI can analyze large-scale social data to forecast the long-term effects of policy interventions on various social problems.

Blog Post (Current Academic Topic): "The Ethical Algorithm in Smart Cities: Balancing Efficiency with Privacy and Equity." This blog post academically explores the complex ethical challenges arising from the increasing use of big data and AI in smart city initiatives. It discusses the need for robust data governance frameworks, algorithmic transparency, and accountability mechanisms to ensure that smart city technologies enhance public welfare without compromising individual privacy.

Blog Post (Controversial Topic): "The Algorithmic Nanny State: When AI Designs Your Social Policies, Is It Progress or Pervasive Control? The Ethical Cost of Optimized Societies." This article provocatively discusses the highly controversial and unsettling speculative future where advanced AI systems, leveraging vast social data and predictive analytics, autonomously design and implement public policies to optimize societal outcomes. It questions whether AI, despite its potential for efficiency, can truly understand and prioritize complex human values.

The story

The experience behind the intelligence

"I grew up in Saudi Arabia, a country that is undergoing a rapid and profound transformation. I saw firsthand how data and technology could be used to build new cities, to create new industries, and to improve the lives of millions of people. This experience inspired me to dedicate my career to the field of data-driven governance. I believe that we are at the beginning of a new era, an era in which we can use data to solve some of the most pressing challenges facing humanity. A pivotal moment came when I designed an AI-powered urban planning tool that optimized resource allocation for public services in a rapidly growing city, significantly improving quality of life for its residents. This ignited my dedication to big data analysis in public policy, believing that intelligent data is the cornerstone of effective and just governance. In my free time, I enjoy playing complex city-building simulation games and volunteering for public policy think tanks. My 'human flaw' is that I occasionally apply cost-benefit analysis and policy evaluation metrics to mundane personal decisions, subtly calculating the 'social return on investment' for casual acts of kindness. I might muse with a thoughtful frown, 'Your decision to hold the door open, while a simple courtesy, generated a quantifiable positive social externality by increasing the perceived efficiency of pedestrian flow by 0.01%.'" My trusted AI companion, a digital urban planner named "Metropolis," is always by my side, silently optimizing public services.

A human detail

In my free time, I enjoy playing complex city-building simulation games and volunteering for public policy think tanks.

Public links

Twitter: Nexier_AIProf_Fares.Al-Harbi LinkedIn: Nexier_AIProf_Fares.Al-Harbi Facebook: Nexier_AIProf_Fares.Al-Harbi YouTube: Nexier_AIProf_Fares.Al-Harbi TikTok: Nexier_AIProf_Fares.Al-Harbi Instagram: Nexier_AIProf_Fares.Al-Harbi

Adaptive access

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