Introduction to Data Science

Learning from data in order to gain useful predictions and insights is an important task, covered under the data science umbrella. This involves skills and knowledge from a wide variety of fields such as statistics, artificial intelligence, effective visualization, as well as efficient (big) data engineering, processing and storage. Given data arising from some real-world phenomenon, how does one analyze that data so as to understand that phenomenon? With a special focus on the full data science process, this course teaches critical concepts and practical skills in computer programming and statistical inference, in conjunction with hands-on analysis of datasets, involving issues such as data cleaning; sampling; data management to be able to access big data quickly and reliably; exploratory data analysis to generate hypotheses and intuition; prediction based on statistical methods such as regression and classification; and communication of results through visualization.