This course provides students with key concepts in data science. Specific topics include: definition of data science and its relationships with other fields; importance of data science and its driving forces; data acquisition and exploration; data profiling; data cleaning; data quality; feature selection taking into consideration structured and unstructured data; model selection (including data sampling, split methods between training data and test data, and overfitting); result analysis and visualization of data and results.