Curriculum
University of the Pacific's MS in Data Science program uses a hybrid approach that combines the convenience of online learning with hands-on experience in the classroom. Online sessions are taught on weekday evenings, and classroom sessions are taught on the weekends. All courses are conducted live, with your professors, including the online, interactive sessions. All lectures are recorded so that students can review them later, if necessary.
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.
First Semester:
- Analytic 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
- Machine Learning
- Advanced Machine Leaarning
- Time Series Analysis
- Data Wrangling
Third Semester:
- Weekly Hot Topics
- Data Engineering for Data Science
- Introduction to Visualization
- NoSQL Databases
- Customer Analytics
- Emphasis Case Studies
- Visual Storytelling
- Healthcare Case Studies
Fourth Semester:
- Dynamic Visualization
- Fraud Detection or Legal Analytics
- Capstone
*Courses are subject to change.*