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Master of Science in Data Science
209.946.2992
datascience@pacific.edu
Dina Dell'Aringa
Administrative Assistant

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Curriculum

The University of the Pacific's MS Data Science program uses a hybrid approach that combines the convenience of online learning with hands-on experience in the classroom. Small classes and personalized attention are trademarks of a Pacific education.

Online sessions are taught on weekday evenings, and classroom sessions are taught on the weekends, in an alternating A-B-A pattern. (click here to see schedule).  Pacific faculty lead all of the courses, including the online, interactive sessions that are recorded so that students can retrieve them later.

The program culminates with the Capstone Project, which gives students the opportunity to apply the knowledge they have gained by working with industry professionals to solve a real-world problem.

The curriculum is the same for both San Francisco and Sacramento programs. New San Francisco cohorts begin classes in the fall, and new Sacramento cohorts begin classes in the spring.

Below courses are subject to change.

First Semester:
- Weekly Hot Topics
- Relational Databases
- Linear Algebra for Data Science 
- Research Methods for Data Science
- Analytics Computing for Data Science
- Frequentist Statistics

Second Semester:
- Weekly Hot Topics
- Bayesian Statistics
- Software Methods for Data Science
- NoSQL Databases
- Introduction to Data Visualization
- Machine Learning for Data Science
Data Wrangling
- Healthcare Case Studies

Third Semester:
- Weekly Hot Topics
- Data Engineering for Data Science
- Emphasis Case Studies
-
 Analytics Storytelling
- Elective (Fraud Detection, Recommender Systems, Text Mining, Customer Analysis, Time Series Analysis, Sentiment Analysis)

Fourth Semester:
- Dynamic Visualization
- Visual Storytelling
- Capstone