This module provides a condensed introduction to the “Data Science Pipeline”, introducing students to methods, techniques, and workflows in applied data analytics and machine learning, including data acquisition, preparation, analysis, visualization, and communication.
Click on the to do for the week to see what you should do to keep up with the module.
W 36: Data Manipulation, Exploratory Data Analysis (EDA), Data Visualization
W 37: Unsupervised Machine Learning (UML), Supervised Machine Learning (SML)
W 38: Workshop & project work