About This Course

This course, based on a UC Berkeley Connector Course connecting Economics and Introduction to Data Science, introduces advanced topics from upper division Economics using practical applications and datasets. It is designed to sculpt a convergence between the realms of Economics and Data Science.

Course Description

This Data Science and Economics course encompasses an introduction to complex topics like the Lorenz Curve and Gini Coefficient, usage of the statsmodels package for econometrics, and working with a finance API to process financial data. Through the introduction of applied datasets, the course endeavors to illustrate intermediate economic concepts practically.

What Students Will Learn

• Implementation of Game Theory and Oligopoly models
• Techniques to measure economic inequality
• Understanding and performing Randomized Controlled Trials for International Development
• Introduction to econometrics and insight on how to analyze econometrics papers
• Construction and analysis of the Marginal Abatement Curve for environmental economics focused on Methane Emissions
• Calculation and application of Present Value in financial contexts
• Practical training on using a finance API to download and manipulate stock price data

Prerequisites or Skills Necessary

• Data 88.1EX: Fundamentals of Economics
• Data 88.2EX: Advanced Concepts in Economics

Course Coverage

• Economics and Data Science interface exploration
• Application of finance API for real-world financial analysis
• Statistical analysis using specialized econometrics software
• Case studies on economic models and their implications in policy making

Who this Course is For

Students and professionals interested in the overlap of economics and data science, especially those looking to understand economic models through a data-driven lens. This course is tailored for learners eager to explore advanced economic concepts through applied data science methodologies.

Application of Skills in Real World

• Developing understanding of economic indicators and models to make informed decisions in policy making or financial sectors.
• Utilizing programming skills and statistical tools for economic research and data analysis.
• Enhancing the ability to interpret complex data sets and derive economically viable insights.

Syllabus

• Introduction to Connecting Data Science with Economics
• Interactive Applications using Finance APIs
• Analytical Techniques in Econometrics
• Case Studies and Applied Projects