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SCI 01 — An Introduction to Data Science

Quarter: Fall
Day(s): Thursdays
Course Format: On campus
Duration: 6 weeks
Date(s): Sep 29—Nov 3
Time: 7:00—8:50 pm
Drop Deadline: Oct 12
Unit(s): 1 Units
Tuition: $295
Limit: 40
Status: Closed
On campus
7:00—8:50 pm
Sep 29—Nov 3
6 weeks
Drop By
Oct 12
1 Units
Living in the information age, we find ourselves surrounded and overwhelmed by data, making it imperative for us to find ways to identify the data we need, classify and organize it, and draw conclusions from it. Data science is a very practical discipline with many applications in business, science, and government, such as targeted marketing, web analysis, disease diagnosis and outcome prediction, weather forecasting, credit risk and loan approval, customer relationship modeling, and fraud detection.

This course presents a high-level overview of three main topics: basic analysis and visualization of data, introductory machine learning concepts, and basic programming in R (a programming language that is widely used for data analysis). By the end of the course, students will be able to apply data science techniques to real-world applications in order to draw meaningful conclusions. The course will include lectures and handson interactive problem-solving. Examples will come from real-world problems in weather, marketing, biology, stocks, neuroscience, medicine, and other disciplines.

No computer science experience is necessary.

Students must be familiar with computer basics. Students are required to bring a Mac or Windows-based laptop computer to class.

Mohammad Shokoohi-Yekta, Data Scientist, Apple

Mohammad Shokoohi-Yekta has worked on predictive modeling projects for Samsung, Bosch, UCLA, and General Electric and has taught at UC Riverside and Cal Poly Pomona. He received a PhD in computer science from UC Riverside with an emphasis on data mining, machine learning, and time series analysis.

Textbooks for this course:

No required textbooks