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Design of experiments (online)

This course empowers data professionals to develop their skillset and effectively set up, run and analyse the outcomes of online A/B tests.

About this course

This online course is a collaboration between UTS and Coder Academy, aimed at data professionals with some existing experience of Python programming, and general knowledge of statistics.

Knowing how to test new websites, different ad campaigns, user interfaces and customer journeys is an essential tool for businesses and organisations looking to improve and grow. Hence, data professionals with these skills will be better positioned to provide additional value to their organisations. The skills gained through this course will make an invaluable asset in their toolkit.

This course provides an intensive end-to-end primer for data professionals and covers both the theory (e.g., objectives models, tools and statistics) and practice (e.g., designing, collecting, analysing, reporting) behind the design of experiments.

For more information on the UTS & Coder Academy course collaboration, or to contact the Coder Academy team directly, follow this link.

Course structure

This intensive course is conducted over two three-hour evening sessions and covers:

  • Introduction to Experimental Design or Design of Experiments (DOE)
    • What are DOEs?
    • The importance of DOEs
    • Objectives of DOEs
    • A/B Testing vs other experiments in business settings and the social sciences
  • Different kinds of DOEs
    • Screening
    • Full factorial
    • Optimisation
  • Best tools for DOEs in Python
  • Overview of the statistics required for DOE
    • Hypothesis testing
    • t-test and chi-square test
    • ANOVA and two-way ANOVA
    • Confounding variables
    • Correlation
    • Power analysis
    • Regression analysis
  • Designing an experiment
  • Collecting the data and setting up your Python environment
  • Analysing the experiment
  • Interpreting and reporting our results
  • Making sure anyone can reproduce our results using the same data


Learning outcomes

  • Describe and prepare experiments
  • Analyse data from experiments (A/B tests) in Python using different techniques
  • Extract insights and create data visualisations from experimental data
  • Understand how to create reproducible results from your analysis


Any questions about the course or what to expect on the day? 

Looking for different dates or a similar course?

Who is this course for?

This course is designed for professionals, data analysts or researchers with a working knowledge of Python who’re looking to set up, run and evaluate online experiments (A/B tests) – attendees might include business analysts, consultants, data analysts, digital marketers, data journalists, librarians, and researchers.



15 September




6 hrs

Meet the Expert

Ramon Perez

Ramon Perez

Ramon is a data scientist and instructor at Coder Academy and a research associate at INSEAD. He works at the intersection of education, data science, and research in the areas of entrepreneurship and strategy. He has previously worked in consumer behaviour and development economics research in professional and academic settings, helping multinational companies understand their customers better and developing new methods to study the levels of financial literacy across the globe. Ramon holds a BSc in economics, finance and marketing, and an MA in Economics. In his spare time, he enjoys cycling, baseball, CrossFit, and finding new coffee shops around Sydney.

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Book a session

Tue 15 Sep 2020 -
Thu 17 Sep 2020
Expert: Ramon Perez
  • Online via Canvas virtual classroom
  • Online
  • 2 sessions, 6 hours total

This online course runs for a small group of up to 50 participants, and registration for each session closes at midnight the day prior to the class.

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