Foundations of Data Science
10:10am–12:40pm
SEELEY W. MUDD BUILDING MUD 833
Morningside
Seat data provenance: Directory as of August 23, 2026 at 4:00 AM
Description
Designed to provide an introduction to data science for sophomore SEAS majors. Combines three perspectives: inferential thinking, computational thinking, and real-world applications. Given data arising from some real-world phenomenon, how does one analyze that data so as to understand that phenomenon? Teaches critical concepts and skills in computer programming, statistical inference, and machine learning, in conjunction with hands-on analysis of real-world datasets such as economic data, document collections, geographical data, and social networks. At least one project will address a problem relevant to New York City
Reviews
Course experience
n=6, 2021–2024
Aggregated across everyone who has taught this course.
Teaching quality
4.5 / 5
Grading fairness
4.0 / 5
Workload
No signal
Difficulty
4.0 / 5 · Hard
Overall sentiment
Mixed
Would take again
Majority say yes
In your week
Where it meets
Flat map — motion reduced
Workload and grading
- Grading
- Not published
- Format
- Not published
- Credits
- 3 credits
Reported workload
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