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FutureLearn

Behavioural Data Science for Decision-Makers

Durham University via FutureLearn

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Overview

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Apply behavioural data science to make better decisions in business

Learn to connect behavioural theory with practical data skills to uncover what shapes decision-making, from customer behaviour to workplace motivation.

Each week, you’ll build your confidence in data collection, analysis, and communicating insights for action.

Ethical approaches to behavioural data

Understand why integrity and privacy matter, and explore real-life dilemmas faced by professionals in sales, marketing, HR, and research.

You’ll learn the legal and ethical foundations of collecting and handling behavioural data in different organisational environments. Implementing ethical data projects that inspire trust and safeguard wellbeing.

Analysing human behaviour with data

Master the essentials for storing, processing, and analysing behavioural data using techniques ranging from simple statistics to machine learning. You’ll see how data points, can reveal deeper cognitive, social, and situational patterns.

You’ll build fluency in choosing indicators and tools that suit your goals, unlocking new understanding in customer engagement, team motivation, or forecasting.

Communicate behavioural insights for action

Masker skills in visualising and presenting behavioural findings with clarity. Learn to shape insights into stories that drive positive change, blending tables, figures, and plain English for every audience.

You’ll walk away with the ability to evaluate and challenge the behavioural claims made by others, so your decisions remain sharp, ethical, and evidence-based.

This course is ideal for anyone keen to use behavioural data for smarter, more ethical decision-making. From business professionals, leaders to analysts in sales, marketing, strategy, and HR.

Syllabus

  • Understanding Behaviour through Data
    • Welcome!
    • Measurement, indicators, and latent variables
    • Decision-Making: An Overview
    • Check your knowledge!
    • Case Study
  • Extracting Value from Data
    • Welcome to week 2!
    • Data Ethics, Hygiene, and Planning for Future Research
    • Traditional methods vs. Big Data and Machine Learning
    • The Complex Realities of Data Analysis - Two Case Studues
  • Communicating Insights and Looking Ahead
    • Welcome to week 3!
    • The Power and Purpose of Data Visualisation
    • Wrap up

Taught by

Vladimir Ponizovskiy

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