Explore Data Science
Data Science examines turning uncertain observations into reproducible evidence. This subject guide introduces the questions, methods and practical work that help learners understand the field before choosing a formal course of study.
A strong starting point is to connect probability with statistical inference. The first develops a foundation for reasoning; the second provides a setting in which to test ideas. Keep a learning journal that records assumptions, sources and questions that remain unresolved.
Four areas to investigate
Probability
Connect probability to the study of turning uncertain observations into reproducible evidence. Compare an introductory explanation with a worked example, then describe where the approach is useful and where it may fail.
Statistical inference
Connect statistical inference to the study of turning uncertain observations into reproducible evidence. Compare an introductory explanation with a worked example, then describe where the approach is useful and where it may fail.
Data engineering
Connect data engineering to the study of turning uncertain observations into reproducible evidence. Compare an introductory explanation with a worked example, then describe where the approach is useful and where it may fail.
Visual analytics
Connect visual analytics to the study of turning uncertain observations into reproducible evidence. Compare an introductory explanation with a worked example, then describe where the approach is useful and where it may fail.
Learn through inquiry
Analyse an open dataset with missing values and communicate the uncertainty of the conclusions.
Begin with a question narrow enough to investigate. Decide what evidence would support an answer, document the method and explain what further work would be needed.