Master of Science in Data Analytics

Program Description/Overview

The Master of Science of Data Analytics (MSDA) degree enables students to learn the techniques and skills needed to work with diverse data sets, a range of analytics platforms and reporting tools, to ultimately tell an actionable data driven story, tell that story right, and tell it right now. 

Students are given the opportunity to roll up their sleeves in structured classroom environments to work directly with top enterprise solutions such as Google Analytics 360 Suite, Adobe Analytics Suite, Python, R, SQL, Hadoop, Moz, Hitwise, IBM CoreMetrics, Gephi, Power BI, Power Pivot, and so much more. Coupled to a dynamic range of statistical data modeling methods and functions, students learn the critical skills required to work with stakeholders and descriptive, predictive, prescriptive, diagnostic and logistical performance outcomes. 

In the emerging fields of Big Data, Data Science, Analytics, and Reporting, analysts are in demand across all vertical industries. The MSDA program puts these roles within the grasp of graduates, including Analytics Associates, Enterprise Analysts, CRM and Customer Journey Analysts, market analysts, data scientists, Optimization Analysts, Supply Chain Analysts, and more.

Emphasis/Concentration/Tracks

Fast Track Program

In the Fast Track program, MSDA students can take up to three (9 units) of doctoral level bridge courses from Alliant’s Doctorate of Business Administration (DBA) program. If students complete the bridge courses with a B or above grade, they can transfer these courses into these doctoral programs if they enroll in them at Alliant International University upon completing their MBA program.

The following Fast Tracks are available for this program:

1. Doctorate in Business Administration (DBA) with Information and Data Science specialization

Program Learning Outcomes/Goals

1. Demonstrate an understanding of techniques for maximizing the value of data in organizations
2. Apply critical thinking skills in the context of problem solving in the business workplace
3. Project a positive, proactive and non-judgmental attitude towards diverse cultural and international identities in interpersonal and professional interactions
4. Demonstrate competence in communicating data solutions to organizational audiences
5. Apply knowledge and skills in data science in the context of the organization
6. Be able to make ethical and socially responsible decisions for data applications in business
7. Leverage teams in the applications of data analytics and information technology

Internship, Practicum, and/or Dissertation Information

Students are required to participate in the internship series as part of their experiential learning within the program. The internship is designed to develop professional practice related skills in student’s program expertise through a variety of work experiences which could involve independently conducted professional projects or an internship. This is designed to provide students with in-depth, supervised practical learning experiences. The internship required may be prior to one academic year in the program. As a result, international students completing the internship series prior to one (1) academic year should contact the International Students Office for details and specialized requirements.

Credit Units

Total Credit Units: 33

Total Core Credit Units: 33

Total Elective Credit Units: N/A

Total Concentration Credit Units: N/A

Prerequisite Courses

This program has two pre-requisite courses that are to be completed during Session 1 and 2 of Year One. Applications for a waiver is to be made to the program academic advisor. For consideration to waive the pre-requisite courses, students must satisfy one of the following requirements:

1. Bachelor Degrees: Students with undergraduate majors including a course in math, a course in statistics and a course in programming are eligible to apply for waivers of the program pre-requisites courses.
   1. A 3-unit equivalent course completed at the Bachelor’s level within the last 3 years in math or in statistics with a grade of B+ or better will waive the DAT50050  pre-requisite course. In cases where the course was completed more than 3 years ago but less than 5 years ago, students can apply for a waiver and the program will assess the course contents.
   2. A 3-unit equivalent course completed at the Bachelor’s level in programming (e.g., C++, .NET/C#, JAVA, R, or Python) within the last 3 years with a grade of B+ or better will waive the DAT50000  pre-requisite course. In cases where the course was completed more than 3 years ago but less than 5 years ago, students can apply for a waiver and the program will assess the course contents.
2. Masters Degrees: Students with a masters including a course in math or statistics, and a course in programming at the masters level, completed with a grade of B or better in the previous 5 years can waive the applicable subject area pre-requisite course for the program.

The prerequisite courses for this program are to be completed during Session 1 and 2 of Year One:

• DAT50000 - Essentials of Informatics Using Python  (3 units)
• DAT50050 - Basic Applied Statistics  (3 units)

Emphasis/Concentration/Track Requirements

Curriculum Plan

The following curriculum plan is a sample and serves only as a general guide. Curriculum plans and course sequence are subject to variation depending on a student’s start term. Students must complete all coursework required for their program as set forth in their individual master plan of study.