The Student Services team will have office hours at Harmony House (561 Lomita Dr, Stanford, CA 94305) on Tuesday and Thursday from 10 a.m. to 4 p.m.
Principles of Data Science
A hands-on introduction to the methods of data science. Strategies for analyzing and visualizing tabular data, including common patterns and pitfalls. Data acquisition through web scraping and REST APIs. Core principles of machine learning: supervised vs. unsupervised learning, training vs. test error, hyperparameter tuning, and ensemble methods. Introduction to data of different shapes and sizes, including text, image, and geospatial data. The focus is on intuition and implementation, rather than theory and math. Implementation is in Python and Jupyter notebooks, using libraries such as pandas and scikit-learn. Course culminates in a final project where students apply the methods to a data science problem of their choice. (Students with experience in another programming language should take CS 193Q to catch up on Python.)
Details:
- Catalog Number
- DATASCI 112-01
- Class Number
- 22670
- Course Cost
- $5488.00
- Population
- High School, Undergraduate, Graduate
- Units
- 4
- Interest Area
- Math and Data Science
- Course Format & Length
- In-Person, 8 weeks
- Instructors
- Alex Dekhtyar
- Dates
- -
- Prerequisites
-
CS 106A or equivalent programming experience in Python
- Schedule
- Mon, Wed, Fri 10:30 AM - 11:20 AM
- Course Notes
-
This course has a required discussion section in addition to the main lecture section.