CTIM 123 — Introduction to Data Science
This course introduces students to Data Science and Big Data. Topics include: visualizing data, linear algebra, statistics, probability, hypothesis and inference, gradient descent, collecting data, working with data, machine learning, k-nearest neighbors, naive Bayes simple linear regression, multiple regression, logistic regression, decision trees, neural networks, deep learning, clustering, natural language processing, network analysis, recommender systems, databases/SQL, MapReduce, and data ethics. Two lecture and two laboratory hours per week.