Azusa Pacific University
Data Science Minor
DURATION
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LANGUAGES
English
PACE
Full time
APPLICATION DEADLINE
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EARLIEST START DATE
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TUITION FEES
USD 20,976
STUDY FORMAT
On-Campus
Introduction
Program at a Glance
The School of Humanities and Sciences offers diverse well-rounded degree programs to prepare critical thinkers to make a difference in the world for Christ.
Program Information
- Program Units: 21-23
- Location: Azusa (Main Campus)
Gain Hands-on Experience
- Explore how your faith can inform ethical decisions in data management and analysis
- Learn how to represent data effectively
- You’ll learn directly from faculty mentors with professional experience
Program Details
The minor in data science comprises a core introductory sequence in statistics, computer science, data ethics, and data visualization, plus three electives chosen from other data-centric and computational courses across departments.
Admissions
Scholarships and Funding
2024-25 Academic Scholarships
| Scholarships | Amount | Class Standing | Renewability |
| Trustees’ Scholarship | Full Tuition | Incoming Freshman | Up to four years |
| President’s Scholarship | $24,000 per year | Incoming Freshman or Transfer | Up to four years |
| Provost’s Scholarship | $21,000 per year | Incoming Freshman or Transfer | Up to four years |
| Deans’ Scholarship | $20,000 per year | Incoming Freshman or Transfer | Up to four years |
| Directors’ Scholarship | $18,000 per year | Incoming Freshman or Transfer | Up to four years |
| Mary Hill Award | $14,000 per year | Incoming Freshman | Up to four years |
Curriculum
Core Requirements
- Introduction to Statistics or Introduction to Modeling with Probability
- Introduction to Computer Science I
- Ethics in Data Analytics
Electives
- Data Visualization
- Data Analytics, Spreadsheets, and Data Visualization
- Data Analysis
- Statistical Models
- Algorithms and Data Structures
- Artificial Intelligence
- Machine Learning
- Foundations of Business Analytics
- Big Data Analytics for Business
- Experimental Research Methods
- Non-Experimental Research Methods
- Analysis of Variance and Analysis of Variance Lab
- Regression and Regression Lab
Total Units 21-23
Program Outcome
Program Learning Outcomes
- Utilize fundamentals of statistical analysis to glean insight from data.
- Utilize fundamentals of computer programming to manage and analyze data.
- Communicate data effectively via visualizations and reproducible reports.
- Engage critically with issues of data ethics from a Christian worldview.
Career Opportunities
- Computer and Information Systems Managers - Plan, direct, or coordinate activities in such fields as electronic data processing, information systems, systems analysis, and computer programming.
- Natural Sciences Managers - Plan, direct, or coordinate activities in such fields as life sciences, physical sciences, mathematics, statistics, and research and development in these fields.
- Clinical Research Coordinators - Plan, direct, or coordinate clinical research projects. Direct the activities of workers engaged in clinical research projects to ensure compliance with protocols and overall clinical objectives. May evaluate and analyze clinical data.
- Water Resource Specialists - Design or implement programs and strategies related to water resource issues such as supply, quality, and regulatory compliance issues.
- Computer and Information Research Scientists - Conduct research into fundamental computer and information science as theorists, designers, or inventors. Develop solutions to problems in the field of computer hardware and software.
- Software Developers - Research, design, and develop computer and network software or specialized utility programs. Analyze user needs and develop software solutions, applying principles and techniques of computer science, engineering, and mathematical analysis. Update software or enhance existing software capabilities. May work with computer hardware engineers to integrate hardware and software systems, and develop specifications and performance requirements. May maintain databases within an application area, working individually or coordinating database development as part of a team.
- Database Architects - Design strategies for enterprise databases, data warehouse systems, and multidimensional networks. Set standards for database operations, programming, query processes, and security. Model, design, and construct large relational databases or data warehouses. Create and optimize data models for warehouse infrastructure and workflow. Integrate new systems with existing warehouse structure and refine system performance and functionality.
- Data Warehousing Specialists - Design, model, or implement corporate data warehousing activities. Program and configure warehouses of database information and provide support to warehouse users.
- Data Scientists - Develop and implement a set of techniques or analytics applications to transform raw data into meaningful information using data-oriented programming languages and visualization software. Apply data mining, data modeling, natural language processing, and machine learning to extract and analyze information from large structured and unstructured datasets. Visualize, interpret, and report data findings. May create dynamic data reports.
- Business Intelligence Analysts - Produce financial and market intelligence by querying data repositories and generating periodic reports. Devise methods for identifying data patterns and trends in available information sources.
- Clinical Data Managers - Apply knowledge of health care and database management to analyze clinical data, and to identify and report trends.