IDS Blog

Discovering Patterns in Transactional Data

by Kunal Sonalkar
June 2024

Image Description As a data scientist, one of the most common tasks you’ll encounter is finding patterns and relationships within large datasets. Let’s consider an example from a supermarket setting. One powerful technique for achieving this is Apriori analysis, which is particularly useful for market basket (shopping cart) analysis and identifying frequent item sets in transactional data.
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Data Science Pipelines

by Dr. James Molyneux
March 2024

A topic that comes up fairly regularly amongst data science professionals is the idea of pipelines. And I can imagine that all of the casual talk about pipes and pipelines probably makes it seem like data scientists are something more akin to plumbers than anything else… which wouldn’t be the worst characterization of the job I’ve ever heard. Continue Reading

Course Overview

Introduction to Data Science – Course Overview
Unit	Unit Title	Unit Description
Unit1	Data and Visualizations	Introduces students to fundamental notions of data analysis—such as distribution and multivariate associations and emphasizes creating and interpreting visualizations of real-world processes as captured by data
Unit2	Distributions, Probability, and Simulations	Students use numerical summaries to describe distributions and introduces probability through the lens of computer simulations for informal inference
Unit3	Data Collection Methods: Traditional and Modern	Prepares students to learn about the various ways of collecting data, including Participatory Sensing, and the effect that data collection has on their interpretation of the patterns theydiscover
Unit4	Predictions and Models	Students learn to make and how to use mathematical and statistical models to predict future observations and how data scientists measure the success of these predictions

Discovering Patterns in Transactional Data

Data Science Pipelines

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