Python for Data ScienceLaajuus (5 cr)

Objective

You will gain a brief understanding of the field of data science and it’s main concepts. After this course, you will know how to collect, process and visualize different types of data using Python and it’s libraries, such as NumPy, Pandas and Matplotlib. The main focus of this course is in practical assignments that are designed to develop your skills especially within the data processing steps of an analytics project. We assume that the students are familiar with have basics of Python. Structures that are more characteristic for Python are discussed.

Content

Main contents of the course: - Programming structures more characteristic for Python - Principles of visual analytics - Reading and writing data - Data structures and their basic properties - Fundamental exploratory analysis of data - Selecting, indexing, grouping and transforming data - Working with missing data and duplicates - Visualizing data with Matplotlib

Assessment criteria, satisfactory (1)

The student: - can apply the skills learned during the studies in a limited manner - is able to recognize and understands theories and tools learned during the study

Assessment criteria, good (3)

The student: - is able to solve given problems by applying the skills learned during the study - is able to analyze relevant theories, and can independently make decisions based on these

Assessment criteria, excellent (5)

The student: - can create more advanced solutions by utilizing the skills learned during the study - assesses relevant theories and can independently apply these in practice