Introduction to Data Science

3 units

This course provides an introduction to data science and machine learning, and it focuses on the practical application of models to real-world supervised and unsupervised learning problems. We will discuss methods for linear regression, classification, and clustering and apply them to perform sentiment analysis, implement a recommendation system, and perform image classification or gesture recognition. One of the main objectives of the course is to become familiar with the data science workflow, from posing a problem to understanding and preparing the data, training and evaluating a model, and then presenting and interpreting the results. We will also touch on concepts such as similarity-based learning, feature engineering, data manipulation, and visualization. The course uses Python, which is currently the most popular programming language for data science. This course does not teach programming in Python.