Syllabus

This course is designed as a companion course to ORIE 5260: Machine Learning, and ORIE 5280, Financial Data Practicum. Students will utilize skills and knowledge from each course to complete projects spanning all three.

Administration

Staff and lectures

Patrick Steele (prs233@cornell.edu). Lectures will take place from 9:00a – 12:00p and 1:00p – 4:00p on January 19 – 23 and January 25 – 28.

Course materials

All materials will be available on this web site or on the course server.

Prerequisites

You should be comfortable programming in at least one imperative language; the course will be taught in Python.

Textbooks

None. There are myriad resources online that we will take advantage of.

Assignments

There will be recitation-style assignments each day, and on-going projects throughout the course. All work will be submitted by creating a web service on the course server; see here for details.

Policy on Academic Conduct

Collaboration is encouraged, although all students are expected to complete their own work.

Topics

• Version control: managing projects with Git
• Working with remote servers
• Unit testing: writing reliable software
• Databases: using relational and non-relational databases
• Exploratory data analysis: using Python and related libraries to explore data sets
• RESTful APIs: interacting with published APIs to extract data from web services
• Web scraping: interacting with websites with no API to extract data