Short Course

by Dr. Hui Lin (Shopify) and Dr. Ming Li (Amazon)

Many aspects of day-to-day data science work are almost absent from the conventional statistics literature and curriculum. Yet these activities account for a considerable share of the time and effort of data professionals in the industry. This short course, "Data Science in Practice," focuses on the practical side of data science and statistical analysis.  

This course aims to increase the visibility of industrial data science-related careers, data workflows, data environment, project cycle, and most common techniques. It is designed for audiences with a statistics education background, and it bridges the gap between traditional statisticians and data professionals in the industry. 

No software download or installation is needed, and the hands-on part is done through the internet browser with hands-on sessions in Databricks and Colab (using PySpark). 

Location: Thornton Hall, Room 404 (4th floor)- Link to Map

Schedule for June 13, 2022:

8-9: Breakfast  

9 - 11:30  

Part one: Data science as a career  

• What are the different tracks of data science? 
• What is the career path in data science? 
• What is the broader quantitative field? 

Part two: Data science project cycle  

11:30 - 12:30: Lunch   

12:30 - 2:30   

Part one: Big data platform, pipeline, and modeling  

Part two: Deep learning in a nutshell   

2:30 - 3:00 break  

3:00 - 4:40 Hands-on exercises