Programming in Python for Data Science

This course is a part of the UBC Key Capabilities in Data Science Certificate Program, and focuses on the foundations of programming in Python for data science, along with data analysis techniques. It provides Python programming skills to process raw data into a format suitable for analysis, to write analysis functions, and to derive data-driven insights by creating visualizations and summary tables. Students work with powerful Python packages made for data science, including Pandas for processing tabular data, Altair for data visualization and NumPy for working with numerical data types. Recipients of this credential are are able to perform the following. 1. Define tidy data and explain why it is an optimal format for data analysis. 2. Clean, filter, manipulate (wrangle) and summarize data using Python libraries for more effective data analysis. 3. Explain fundamental programming concepts such as loops, iteration, flow control, program design, conditionals, and data structures that create a solid foundation in data science programming. 4. Import files and coding style guides.