Foundation in Behavioural Data Science

Foundations in Behavioural Data Science

Behavioural data science blends insights from psychology, economics, and analytics to understand and influence human decisions using digital data. This course, titled Foundations in Behavioral Data Science, introduces participants to practical tools such as digital footprint analysis, nudging strategies, and A/B testing. Designed for professionals in marketing, HR, and product development, the course focuses on using behavioural signals and ML methods to improve user engagement, communication design, and intervention strategies. It addresses the growing demand for data-informed behavioural insights across sectors.

Incentives available for groups and teams of four or more attending open enrollment programs

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This course is ideal for professionals in marketing, HR, product management, customer experience, or consumer analytics roles. It is targeted at beginner to intermediate participants who want to apply behavioural insights using data. Participants should have basic familiarity with business data and an interest in human-centred design or engagement analytics.
- Demonstrate an understanding of behavioural economics principles and their relevance to digital user behaviour and data-driven decision making.
- Identify and interpret digital traces such as clickstreams, navigation paths, and engagement signals to uncover behavioural patterns.
- Apply A/B testing frameworks to design, run, and evaluate behavioural experiments across marketing, HR, or product contexts.
- Design and critique nudging strategies that influence user choices while maintaining ethical and human-centred approaches.
- Use behavioural signals and sentiment analysis to improve communication design, personalisation efforts, and engagement strategies.
- Collaborate effectively with data scientists, UX designers, and marketing teams by integrating behavioural thinking into data-informed interventions.
- Evaluate the ethical implications of behavioural data use, including concerns around manipulation, consent, and bias.
- Translate behavioural insights into actionable strategies to enhance user experience, product design, and organisational impact
M1: Behavioural Science Principles and Data Use
Explore foundational concepts from behavioural economics and understand how they can be applied to real-world data for decision-making and user engagement.
M2: Digital Traces and User Footprint Analytics
Learn how to identify, clean, and interpret digital behavioural data such as clickstreams and user navigation paths to uncover actionable insights.
M3: Designing and Evaluating A/B Tests
Gain hands-on experience in designing controlled experiments to test behavioural interventions and evaluate their impact using data-driven methods.
M4: Nudging for Product, HR, and Marketing Goals
Discover how to create and tailor nudging strategies that influence user behaviour in specific organisational contexts like recruitment, retention, and customer conversion.
M5: Ethics and Behavioural Design Critique
Critically assess the ethical considerations, potential biases, and design implications when applying behavioural science to digital products and services.
Ir. Dr. Manjeevan Singh Seera
PhD in Computational Intelligence, Universiti Sains Malaysia
Associate Professor, School of Business, Monash University Malaysia
HRDCorp Trainer Number: 16092
Dr. Seera is an accomplished academic and industry expert specializing in machine learning, predictive analytics, and sustainable energy solutions. He has extensive experience in delivering training programs for financial institutions, equipping professionals with advanced analytics skills to drive decision-making and operational efficiency.

Education and Training Academy

Education and Training Academy

Foundation in Behavioural Data Science

Foundations in Behavioural Data Science