The Master of Science in Analytics online program will prepare you to manage data from a variety of sources, use analytical tools to gain insights from data, and effectively model and communicate findings and results to key stakeholders and decision-makers within your organization.
Program Highlights:
- Enables students to manage a wealth of data, gain insights from data and communicate findings to key decision makers.
- Gain practical knowledge in predictive and prescriptive analytics, data visualization and modeling, machine learning, database management, research and more.
- Can be completed entirely online in as little as two years.
Program learning goals and student learning outcomes
Program Mission: To prepare students for leading roles in analytics.
Creighton-formed business leaders will:
PLG 1: Exhibit disciplinary knowledge in Analytics.
SLO 1A: Develop visualizations of data.
SLO 1B: Create relational databases.
SLO 1C: Evaluate a variety of analytics tools and techniques.
SLO 1D: Analyze data with appropriate modeling techniques to support fact-based decision-making.
PLG 2: Think critically to aid decision-making.
SLO 2A: Apply problem-solving skills in diagnosing and addressing business challenges.
PLG 3: Communicate professionally.
SLO 3A: Effectively communicate analytical conclusions in a written and visual format.
SLO 3B: Articulate assumptions, analyses and interpretations of data in an oral format.
PLG 4: Commit to action that demonstrates care for others.
SLO 4A: Analyze a business ethics situation and propose a course of action.
SLO 4B: Demonstrate knowledge of strategies to work effectively with others on diverse project teams.
PLG 5: Exhibit personal habits consistent with leadership formation.
SLO 5A: Reflect on and articulate the relationships among personal values, professional obligations, and social responsibilities.
MS-Analytics requirements: 33 credits
Code | Title | Credits |
---|---|---|
Core required courses | ||
ANX/BIA 603 | Python Programming for Analytics | 3 |
ANX/BIA 729 | Statistics for Data Scientists | 3 |
ANX/BIA 755 | Data Wrangling | 1.5 |
ANX/BIA 775 | Ethics in Data Analytics | 1.5 |
ANX/BIA 742 | Predictive Analytics | 3 |
ANX/BIA 772 | Data Visual Analysis & Visualization | 3 |
ANX/BIA 781 | Machine Learning | 3 |
ANX/BIA 782 | Database Management Systems | 3 |
Floating Courses (12 hours) May be chosen from list below or new topics assigned by Director | 12 | |
Application of Optimization Modeling | ||
Data Governance | ||
Data Warehousing and Advanced Database Systems | ||
Business Intelligence & Analytics Readings | ||
Total Credits | 33 |