Course Schedule - Spring Semester 2026

     

Meeting location information can now be found on student schedules in ESTHER (for students) or on the Course Roster in ESTHER (for faculty and instructors).
Additional information available here.

ECON 632 001 (CRN: 24520)

COMPUTATIONAL ECONOMICS

Long Title: DATA TOOLS FOR COMPUTATIONAL ECONOMICS
Department: Economics
Instructor: Coleman, Chase
Meetings:
11:00AM - 11:50AM F (12-JAN-2026 - 24-APR-2026) 
1:00PM - 3:30PM F (12-JAN-2026 - 24-APR-2026) 
Part of Term: Full Term
Grade Mode: Standard Letter
Course Type: Lecture/Laboratory
Language of Instruction: Taught in English
Method of Instruction: Face to Face
Credit Hours: 4
Course Syllabus:
Course Materials: Rice Campus Store
 
Restrictions:
Must be enrolled in one of the following Level(s):
Graduate
Section Max Enrollment: 24
Section Enrolled: 0
Enrollment data as of: 24-NOV-2025 7:17PM
 
Additional Fees: None
 
Final Exam: GR Course-Dept Schedules Exam
 
Description: This course teaches the foundational skills necessary to do modern data analytics using the Python programming language. We assume that students have previously worked with Python. We will add to existing Python skills and teach the core scientific and data-specific libraries (numpy, scipy, matplotlib, and pandas). We will use these skills to analyze a variety of economics and social science datasets and answer research and business questions. Recommended Prerequisite(s): Students should have prior experience using the Python programming language before starting this course. Throughout this course we will leverage programming skills such as control flow constructs (if/else, for/while), defining custom functions (def), and finding help on existing functions (? in Jupyter environments and help elsewhere). Although a course in probability or statistics is not a prerequisite, students will find some knowledge of these topics to be helpful. Mutually Exclusive: Cannot register for ECON 632 if student has credit for ECON 208.