Data Analytics, MS

Program Overview

The Master of Science in Data Analytics equips students with advanced skills to apply analytics to real-world problems. The program emphasizes the data analytics process lifecycle, from data exploration to model building and validation. Students can choose between a thesis or project as their culminating experience, preparing them for careers as data analysts, business intelligence analysts, and other data-driven roles across various industries.

Program Outline

Degree Overview:

Overview:

The Master of Science in Data Analytics, offered by the Department of Applied Data Science, is designed in collaboration with industry experts and targets students from diverse academic and professional backgrounds. The program equips students with the advanced skills necessary to apply analytics to solve real-world problems by immersing them in the full data analytics process lifecycle.

Objectives:

• To provide students with a comprehensive understanding of the data analytics process lifecycle.
• To develop students' skills in identifying domain-specific problems, defining requirements, and establishing measurable organizational objectives.
• To impart knowledge and proficiency in data exploration, preparation, visualization, and governance.
• To equip students with the ability to apply programming, statistics, database, data mining, and machine learning technologies to build models for descriptive, diagnostic, predictive, and prescriptive data analytics.
• To train students in the development, validation, and monitoring of data analytics systems to meet requirements and objectives.

Program Description:

The program is designed to prepare students for careers in data analytics across various industry domains, recognizing the strategic importance of analytics in contemporary organizations. It emphasizes the interrelationship between domain data knowledge and emerging information technologies.

Outline:

Core Courses (18 units):

• DATA 220 - Mathematical Methods for Data Analytics (3 units)
• DATA 225 - Database Systems for Analytics (3 units)
• DATA 230 - Data Visualization (3 units)
• DATA 240 - Data Mining and Analytics (3 units)
• DATA 245 - Machine Learning Technologies (3 units)
• DATA 270 - Data Analytics Processes (3 units) (GWAR - Graduation Writing Assessment Requirement)

Elective Courses (6 units):

• Six units of 200-level elective courses selected in consultation with the graduate advisor.

Culminating Experience (6 units):

• Choose one of the following options:
• Plan A (Thesis):
DATA 299A - MSDA Thesis I (3 units) and DATA 299B - MSDA Thesis II (3 units)
• Plan B (Project):
DATA 298A - MSDA Project I (3 units) and DATA 298B - MSDA Project II (3 units)

Assessment:

Graduation Writing Assessment Requirement (GWAR):

• Students must pass the GWAR, which is satisfied by completing the DATA 270 course.

Culminating Experience:

• Students must complete either a thesis or project as part of their culminating experience.
• The thesis must meet university requirements and be written under the guidance of a thesis committee.
• The project is a research or development effort performed by a team of students on a topic approved by an advisor and the instructor of DATA 298A.

Teaching:

Teaching Methods:

• The program is offered in a hybrid format, with courses delivered both in-person and online.

Faculty:

• Full-time tenured or tenure-track faculty members from the Department of Applied Data Science and collaborating departments.

Unique Approaches:

• The program emphasizes the practical application of analytics to real-world problems.
• Students work on projects that involve collaboration with industry partners.
• The program is designed to prepare students for careers in data analytics in various industry domains.

Careers:

Potential Career Paths:

• Data Analyst
• Data Administrator
• Business Intelligence Analyst
• Information Research Scientist

Other Career Opportunities:

• The program prepares students for careers in data analytics across almost all industry domains.