This course provides students with an extensive exposure to the use of Python specifically for data science. Topics include Python language fundamentals, data analysis using Python libraries, applied machine learning and text mining in Python, and the practice of scientific computing. The students will acquire hands-on experience using Python and the popular packages related to data manipulation, processing and analysis, with the minimal backgrounds of theories in methodology aspects. The students are required to be able to independently develop Python codes from scratch in professional way for elementary algorithms in data sciences.

Examination: The students will utilize Python libraries and write Python programming codes to perform basic data manipulation, analysis and visualization tasks and solve practical problems in order to demonstrate their programming skills. Note: To pass the course, apart from obtaining a minimum of 40% in the overall mark, a student must also obtain a minimum mark of 30% in both continuous assessment and examination components.