KINT 8095 - Advanced Python for Social Scientists

This course consists in a follow up to the “Introduction to Python (for Social Scientists)” course and is aimed at consolidating one's skills in order to be able to use the Python programming language in real-life use-cases geared towards social sciences. As such, after a short review of what was learned in the fall semester and making sure everyone has a solid understanding of python's mechanisms, students will experiment with various topics such as web scraping, crawling, API usage, data manipulation, machine learning, data visualization, fuzzy matching, database administration etc. This course will also be the occasion to approach broader computer science topics such as algorithmics, scaling, graph theory etc.

Learning Outcomes

1. Advanced programming skills in Python

2. Basic skills in computer science

3. Data science literacy

4. Insights about engineering tasks for research

Professional Skills

Ability to develop scripts written in Python to solve real-life data science problems. Related skills will be equally useful for a career in academia, in the public/international sector or in the private sector.

Guillaume PLIQUE

Séminaire

English

- In Class Presence: 4 hours a week / 24 hours a semester - Research and Writing for Individual Assessments: 4 hours a week / 48 hours a semester

Having followed the “Introduction to Python (for Social Scientists)” course in the fall or having some preexisting skills in Python is advised.

Students are also expected to attend the class with a proper computer (not a tablet or a pad, as it can be very complicated to develop and execute custom scripts on those). Some alternatives can be provided using cloud services in case a student does not possess a fitting computer.

Spring 2022-2023

Advanced Python for Social Scientists

One or two individual assessments that will consist of full use-cases where students have to solve a problem using python scripts. The scripts, their documentation and the resulting data, typically, will be graded and will count toward 90% of the total grade. Participation will also be graded as 10% of the total grade.

This course is geared toward 10-20 students and as such, a lot of time is dedicated to coaching students individually when they start working on the numerous use-cases and exercises of the course. We will therefore have plenty of time for individual feedback.