Introduction to Data Science
Course code: CS1503. Subject: computer science and introductory data science.
At a glance
Introduction to Data Science
Course code: CS1503. Subject: computer science and introductory data science.
The course is associated with instruction based in the Science and Technology Laboratory Building, West Campus.
Core concepts and course context
Introduction to Data Science | Core concepts and course context
Introduction to Data Science addresses how observations become structured data and how analytical models support interpretation. Students encountering the field benefit from understanding data cleaning, exploratory summaries, classification and the distinction between prediction and causal explanation. Ethical treatment of data and reproducible computation are equally important. The available course record identifies code CS1503 and links teaching activity to the Science and Technology Laboratory Building on West Campus.
Data collection, modeling and reproducible analysis
Introduction to Data Science (CS1503) develops the ideas needed to move from raw observations to reproducible analysis. Data collection, cleaning, descriptive statistics and visualization are distinct stages; machine-learning predictions add a further requirement for train/test separation and error assessment.
Data provenance and the choice of a target variable influence whether a numerical pattern can be interpreted meaningfully.
A closer look at Introduction to Data Science
Introduction to Data Science presents the complete analytical cycle: framing a question, collecting and cleaning data, exploring patterns, building models and communicating results. Responsible work includes documenting sources, checking uncertainty and avoiding conclusions beyond the evidence. Statistical reasoning and computational practice reinforce one another throughout the process.
Independent course study guide
Work from data cleaning and exploratory plots toward clearly evaluated models.
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