This course is a lecture series on data science, economics, programming, and how they can be used to understand the world around us.
We envision this as a complement to econometrics. We focus on learning practical programming skills for the workplace and future studies in economics and finance.
Unlike courses in computer science, data science, or statistics, the emphasis of this course includes both the programming and the statistics necessary to analyze data and subsequently interpret results through the lens of economics.
While anyone with the appropriate prerequisites will benefit from this course, undergraduate programs will find the lecture series suitable for 2nd to 3rd year students who have taken two calculus classes and their school’s equivalent of Econ 101. No prior programming experience is required.
Students who complete this course will be prepared to:
To get an idea of what one can do after taking this course, please take a look at previous student projects.
The essential outcome of the course is: Students will be able to recognize and understand the connections between economic theory and the practice of data science, expanding beyond atheoretical statistical approaches.
The course is divided into three segments.
The first segment of this course covers programming and basic scientific computing in Python by re-examining basic Econ 101 concepts and models.
This provides a natural introduction to thinking of economics as a quantitative discipline, with principles and applications grounded in real world problems.
The second segment dives into data analysis and data science, with the associated data wrangling skills, as a way to leverage economic data, tools, and concepts.
The final segment is a sequence of case studies designed to help students answer specific questions and recommend solutions.
Students will learn and apply more advanced techniques and models, as well as examine new data sources.
While we have kept the prerequisites to a minimum, some degree of mathematical fluency is required.
Most importantly, while familiarity with computers is expected, no programming knowledge is required for this course.
To summarize the background we expect that you should have at least: (1) an introductory “ECON 101” class; (2) one to two terms of calculus; and (3) either an elementary course in matrix algebra, or a willingness to learn the basics on your own.
You should have one course (and possibly two, depending on your university) in Calculus.
The core concepts used throughout the lectures are
If you have not taken a first course in applied linear algebra or matrix algebra, you will need to learn concepts of
Basic probability is sometimes covered in a second calculus course, but if you have never encountered the topics, then review
While more economics is always better, we will try to assume an “Econ 101” background.
Otherwise, we will try to provide additional background material on the economics topics.