CS-E407501 - Special Course in Machine Learning, Data Science and Artificial Intelligence D: Elements of Causal Inference, Lectures, 13.9.2021-10.12.2021
This course space end date is set to 10.12.2021 Search Courses: CS-E407501
Översikt
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Responsible teacher: Pekka Marttinen
Teaching assistants: Caglar Hizli, Onur Poyraz
Contact: by default please use the Slack (link is provided at the bottom of this page). Email addresses for all course personnel are of the form: firstname dot lastname at aalto dot fi).
Periods I-II
Description: We will read the book "Elements of Causal Inference: Foundations and Learning Algorithms" by Peters et al. (https://mitpress.mit.edu/books/elements-causal-inference) and meet once a week to discuss what we have read.
Format:
For 3 credits:
-Reading the book (approximately 200 pages)
-Weekly meetings to discuss (10 times 1 hour)
-A small writing task to prepare before each meeting (writing down the main points, questions, and comments of the section read)
For 5 credits:
-In addition to the above, solving selected problems from the book and attending exercise sessions (5 times 2 hours). Before the exercise session each student returns his/her solutions with the idea that he/she is willing to present the solutions to other students.The course is organized in Zoom. Having a camera on during the meetings is recommended. The meetings will usually take place on Wednesdays from 2 to 3 pm, and the first meeting is on Wednesday, Sep 15. More information about meeting times can be found on the "Lectures" page and more information about the exercise sessions on the "Assignments" page. Please prepare already for the first meeting by reading the book and completing the preparatory writing task (see details in Lectures and Writing tasks).
Grading pass/fail. Passing requires the whole book to be read, all preparatory writing tasks completed, and actively participating in at least 9 face-to-face meetings (missing more meetings requires e.g. a doctor's note). For 5 credits, at least 70% of the assignments must be returned (and demonstrate a fair attempt to solve the problem) and the student must be available to present the solutions of his/her returned assignments in exercise sessions.
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Link to join Slack URL
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