|Course Title||Data Science – Introduction
|Prerequisites||Python I, Python 2 (optional), programming experience|
|Target Audience||All those interested in an introduction to the world of data science. Students must have programming background. See prerequisites.|
|Dates||January 10-17-24-31; February 7-14-21-28, 2018|
|Instructor||José Rafael Porras|
|Schedule||Wednesday: 6:30 p.m. – 9:30 p.m.|
|Gouvernement du Québec fee||$48.00|
|General public fee||$386.32|
Recommended textbook: Class Notes
NB: Certificate provided for all participants who have completed 80% of course hours
|Please note that this is a non-credit course.|
|This course is the first in a series of three courses on the subject of data science. The course will introduce the participant to the concepts of data extraction, transformation and loading using the Python Pandas data science library as well as the R programming environment and SQL.
The course will also explore concepts of data gathering, APIS, JSON and basic web scraping. Beyond ETL concepts, the course will introduce the basics of data visualization and statistical concepts as applied to both R and Python. The course will end with an introduction to regression and other data exploration techniques.
Prerequisites: Python I
|Topics Covered in this Course|