Section 1: General overview
Lecture 1: Introduction to AI governance
Lecture 2: Ethics of AI
Lecture 3: AI and public policy
Section 2: Socioeconomic perspective
Lecture 4: Data privacy and surveillance
Lecture 5: Bias, fairness, and accountability
Lecture 6: Global perspectives on AI governance
Lecture 7: AI in public services and administration
Lecture 8: Law enforcement and AI
Lecture 9: AI and social justice
Section 3: Environmental perspective
Lecture 10: Regulatory frameworks for AI in environmental policy
Lecture 11: AI and public-private partnerships in environmental policy
Lecture 12: AI in energy policy and sustainable development
Lecture 13: Future directions in AI and environmental policy
Lecture 14: AI and intergenerational sustainability
Lecture 15: Course review and future directions
Textbooks:
Muller, V. (2022). AI Ethics and Governance: Navigating the Regulatory Landscape. Palgrave Macmillan.
Russell, S., and Norvig, P. (2020). Artificial Intelligence: A Modern Approach. Pearson Education.
Section 1: Data preparation with R
Lecture 1: Introduction to data science
Lecture 2: The basics of Python and R
Lecture 3: Downloading RStudio and basics of coding in R
Lecture 4: Importing packages and getting data into R
Lecture 5: Saving output and setting up graphics in R
Section 2: Data preparation with Python
Lecture 6: Downloading and basics of coding in Python
Lecture 7: Importing packages and getting data into Python
Lecture 8: Saving output and setting up graphics in Python
Section 3: Regressions with R and Python
Lecture 9: Summary statistics
Lecture 10: Scatter plot, box plot and histogram
Lecture 11: Probit and logit models
Lecture 12: Topics in causal inference
Lecture 13: Topics in spatial data science
Lecture 14: Topics in Bayesian econometrics
Lecture 15: Topics in machine learning
Textbooks:
Wooldridge, J. (2020). Introductory Econometrics: A Modern Approach, 7th Edition. CENGAGE.
Angrist, J. and Pischke, J. (2009) Mostly harmless econometrics: An empiricist’s companion. Princeton University Press.
Imai, K. (2017) Quantitative social science: An introduction. Princeton University Press.
Section 1: Foundation to Environmental Economics
Lecture 1: The environment and economics
Lecture 2: Normative and positive economic analysis
Lecture 3: Social choice: How much environmental protection?
Lecture 4: Efficiency and markets
Lecture 5: Market failure: Public goods, public bads and externalities
Lecture 6: Making decisions about environmental programs
Lecture 7: Demand for environmental goods
Lecture 8: Hedonic price methods
Section 2: Regulating Pollution
Lecture 9: Regulating pollution
Lecture 10: Emission prices and fees
Lecture 11: Property rights
Lecture 12: Audits, enforcement and moral hazard
Lecture 13: Voluntary actions and agreements
Section 3: Advanced Topics
Lecture 14: Managing risk and uncertainty
Lecture 15: Environment, growth and development
Textbooks:
Section 1: What is Future Design
Lecture 1: Introduction to future design
Lecture 2: Future design: Combination of three academic disciplines
Lecture 3: Future design: From the perspective of economics
Lecture 4: Future studies
Lecture 5: Scenario planning
Lecture 6: Originality of future design
Section 2: Future Design and Sustainable Development
Lecture 7: Population growth and well-being
Lecture 8: The environment and economics
Lecture 9: The quality of the environment
Lecture 10: Globalization and the environment
Lecture 11: Market failure: Public goods, public bads and externalities
Lecture 12: Future failures: Disruption of \(C\) cycle and \(N\) cycle
Lecture 13: The economics of biodiversity
Lecture 14: The economics of climate change
Lecture 15: Environmental goods valuation
Textbooks:
Section 1: Foundations of geographic data in R
Lecture 1: R packages for GIS
Lecture 2: Processing shapefiles in R
Lecture 3: Basic maps with R
Lecture 4: Part 1_spatial data operations
Lecture 5: Part 2_spatial data operations
Section 2: Extensions and intermediate techniques in R
Lecture 6: Part 1_World map
Lecture 7: Part 2_World map
Lecture 8: Part 1_Japan regional map
Lecture 9: Part 2_Japan regional map
Lecture 10: Part 1_United States regional map
Lecture 11: Part 2_United States regional map
Section 3: Applications to real-world problems
Lecture 12: Part 1_Geospatial data analysis
Lecture 13: Part 2_Geospatial data analysis
Lecture 14: Part 3_Geospatial data analysis
Lecture 15: Part 4_Geospatial data analysis
Textbooks:
Lovelace, R., Nowosad, J., and Muenchow, J. (2019). Geocomputation with R. CRC Press.
Comber, L., and Brunsdon, C. (2020). Geographical data science and spatial data analysis: An Introduction in R. Sage.
Section 1: Introduction to International Economics
Lecture 1: Basics of international economics
Lecture 2: Introduction to international trade
Lecture 3: Reasons of international trade
Lecture 4: International trade models
Section 2: International Trade Policy
Lecture 5: The instruments of trade policy
Lecture 6: The political economy of trade policy
Lecture 7: Trade policy in developing countries: Part A
Lecture 8: Trade policy in developing countries: Part B
Section 3: Open-economy Macroeconomics
Lecture 9: Globalization, trade and environment
Lecture 10: Macroeconomic analysis of trade balance
Lecture 11: National income accounting and the balance of payments
Lecture 12: Money, interest rates, exchange rates and the Federal Reserve
Section 4: International Macroeconomic Policy
Lecture 13: Economic geography
Lecture 14: Developing countries growth, crisis and reform
Lecture 15: International trade and biodiversity
Textbooks:
Krugman, P. (2018). International economics: Theory and policy. New York: Prentice Hall.
Krugman, P., Obstfeld, M., and Melitz, M. (2018). International trade: Theory and policy. Boston: Pearson Education
Updated on: 2024-11-15