Programming, data extraction and visualisation
The aim of this course is to equip the students with basic tools in programming, data extraction and visualization of datasets. Using a learning-by-doing approach, we solve basic problems encountered in data science using Python. The course will be using a blended learning approach with a focus on solving practical problems under guidance by teachers. Data examples for business applications will be given.
The following three topics will be covered simultaneously using applied programming projects, lectures and web-based learning.
- Basics of Python
- Reading and writing data with Python.
- Accessing sub-sets of a dataset, changing parts of the data, etc.
- Automating tasks in Python (looping, and control structures such as "if, else" etc).
- Basic statistics
- Fundamental theory on data types, data collection, and data quality.
- Communicating statistical results.
- Exploratory analysis
- Computing summary statistics, key numbers, proportions and other descriptive with Python.
- Visualization techniques, including basic statistical plots and their interpretation, scatter-plots, and basic plots for multivariate data.
- The basics of cluster analysis.
This is an excerpt from the complete course description for the course. If you are an active student at BI, you can find the complete course descriptions with information on eg. learning goals, learning process, curriculum and exam at portal.bi.no. We reserve the right to make changes to this description.