I 310D : Introduction to Human-Centered Data Science
Areas
Skills
Topics
Instructor Description
I310D- Introduction to Human-Centered Data Science is a survey course that introduces students to the theory and practice of data science through a human-centered lens, with emphasis on how design choices influence algorithmic results. Students will gain comfort and facility with fundamental principles of data science including (a) Programming for Data Science with Python (b) Data Engineering (c) Database Systems (d) Machine Learning and (e) Human centered aspects such as privacy, bias, fairness, transparency, accountability, reproducibility, interpretability, and societal implications. Each week’s class divided into two segments: (a) Theory and Methods, a concise description of theoretical concept in data science, and (b) Tutorial, a hands-on session on applying the theory just discussed to a real-world task on publicly available data. We will use Python for programming and cover Python basics in the beginning of the course. For modules related to databases, we will use PostGre SQL.
Prerequisites
Informatics 301.
Instructor | Topic Title | Year | Semester | Syllabus |
---|---|---|---|---|
Abhijit Mishra | 2025 | Spring Term | ||
Abhijit Mishra | 2024 | Spring Term | Syllabus | |
Abhijit Mishra | 2024 | Fall Term | Syllabus | |
Abhijit Mishra | 2023 | Spring Term | Syllabus | |
Abhijit Mishra | 2023 | Fall Term | Syllabus | |
Maggie Engler | 2022 | Spring Term | Syllabus | |
Maggie Engler | 2022 | Fall Term | Syllabus | |
Tony Grubesic | 2021 | Spring Term | Syllabus | |
Tony Grubesic | 2021 | Fall Term | Syllabus |
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