Course materials for ECON407 Winter 2019

In reality: you are guinea pigs for the new course (where here we will emphasize slightly more macro content)

• ECON323 "Quantitative Economic Modeling with Data Science Applications"
• Testing out a new textbook "QuantEcon DataScience: Introduction to Economic Modeling and Data Science"

Previous programming experience and classwork is useful, but not required.

However, for those coming in with advanced Python skills, you can use this as an opportunity to learn Julia and/or R for the first parts of the course

Computational Setup

You will not need to install any software on your local computer. You can use the online Jupyter environment from Syzygy To setup, go to ECON407 Syzygy Setup

In the next few weeks, we will give you an HTML and additional repository with a similarly easy setup

For students doing Julia self-study for the first part of the course, setup on the VSE syzygy QuantEcon Julia Setup

• Note, this is on a different jupyterhub for now
• There is a bug in the display of some images on jupyter lab. You can look at the Lecture HTML instead
• You already have Jupyter installed, so start with Using Jupyter rather than the desktop setup.

Syllabus

See Syllabus for more details

Major course sections

1. Python Fundamentals
2. Scientific Computing and Economics
3. Introduction to Pandas and Data Wrangling
4. Data Science Case Studies and Tools

Lectures and Notebooks

1. January 3rd - Intro and pyfun/Basics
2. January 8th - pyfun/Collections and start pyfun/Control Flow
3. January 10th - Finish Pyfun/Control Flow and start Pyfun/Functions
4. January 15th - Scientific/Numpy and Scientific/Plotting
5. January 17th - Scientific/LinAlg and Scientific/Randomness
6. January 22nd - Review PS2 and Scientific/Optimization
7. January 24th - Finish Scientific/Optimization and Introduce Pandas
8. January 29th - Pandas: Intro and start Basics
9. January 31st - Review of PS3, Pandas: Basics
10. February 5th - Pandas: Index and intro to Storage Formats and Data Cleaning
11. February 7th - Review PS4, Pandas: Reshaping
12. February 12th - snow day
13. February 14th - Pandas: Group-by, merging
14. February 26th - Pandas/matplolib visualization (Paul takes over)
15. February 28th - Begin applications/visualization_rules
16. March 5th - Finish applications/visualization_rules, begin applications/regression
17. March 7th - Intro to regression methods, lasso: applications/regression
18. March 12th - Regression forests, neural networks: applications/regression
19. March 14th - More visualization and introduction to classification: applications/recidivism
20. March 19th - applications/recidivism continued
21. March 21st - More classification: applications/classification
22. March 26th - Machine learning in economics-estimating nuisance functions: applications/ml_in_economics
23. March 28th - Machine learning in economics-heterogeneity: applications/ml_in_economics
24. April 2nd - Mapping: applications/mapping
25. April 4th - Working with text: applications/avalanche

Problem Sets

1. January 11th - Problem Set 1 (uploaded as executed ipynb through Canvas)
2. January 17th (class-time) - Problem Set 2
3. January 24th (class-time) - Problem Set 3
4. February 1st - Problem Set 4
5. February 8th - Problem Set 5
6. February 28th - Problem Set 6
7. Probelm Set 7
8. Problem Set 8

Lecture and problem set notebooks can be found in https://github.com/QuantEcon/quantecon-notebooks-datascience.