Program Description/Overview
This program prepares students for rewarding careers by enhancing analytical skills, providing hands-on and applied skills, and giving extensive practical experience in applying these skills, particularly in managerial decision-making contexts. The degree is designed to offer flexibility to students who have prior work experience. The program follows a cohort model, with all students taking the core curriculum courses as a cohort at the beginning of the program. Applied and academic perspectives are combined in the design, development, and delivery of the coursework. Courses are delivered in a in evening classes, once a week to offer flexibility to the diverse student population.
Core concepts include the application of statistical modeling, data warehousing, data mining, programming, forecasting and operations research techniques to the analysis of problems of business organization and performance. Instruction in optimization theory and mathematical techniques, data mining, data warehousing, stochastic and dynamic modeling, operations analysis, and the design and testing of prototype systems and evaluation models is provided.
The program is not yet Title IV approved; therefore, students enrolling in this program are not eligible for federal financial aid at this time, but may apply for private education loans through an outside lender.
Program Learning Outcomes/Goals
- Demonstrate an understanding of techniques for maximizing the value of data in organizations
- Apply critical thinking skills in the context of problem solving in the business workplace
- Project a positive, pro-active and non-judgmental attitude towards diverse cultural and international identities in interpersonal and professional interactions
- Demonstrate competence in communicating data solutions to organizational audiences
- Apply knowledge and skills in data science in the context of the organization
- Be able to make ethical and socially responsible decisions for data applications in business
- Apply methods to collect, analyze, and critically evaluate data and information technology
Program-Specific Admission Requirements
Applicants must satisfy the requirements stipulated in the “Admissions and Registration” section of the University catalog, and must also meet the following criteria:
GPA: Applicants need to meet one of the following GPA requirements
- Overall Bachelor’s GPA is 2.75 or above, or
- Overall Bachelor’s GPA is between 2.60 and 2.75, plus a Minimum five (5) years professional work experience, or
- Minimum GPA of 2.75 in the last 60 units of coursework (include graduate work) completed, or
- An accredited master’s degree with overall GPA 3.0 or above
Resume: A current resume is required
Recommendations: Encouraged but not required
Personal essay (max. 2 pages): an autobiographical statement with future professional plans, the associated professional organizations and honors, activities and other accomplishments.
English Proficiency (International applicants)
- CSML will admit students with IELTS score of 6.0 with no individual band score below 5.5 (or equivalent). Students can start their academic program immediately on entry into their program.
- CSML will conditionally admit students with IELTS score 5.5-5.9 with no individual band score below 5.5 (or equivalent). Students will start in an English program and upon successful completion will start their academic program
- Students with IELTS scores 5.0-5.4 will be admitted to a full ESL program. Upon successful completion of the ESL program, they will start their academic programs.
Upon receipt and review of all documentation, the candidate will be considered for final admission. Final admissions decision will be made by the Program Faculty.
Note that students may apply for admission in the final year of their undergraduate program if they are confident they will meet the admission requirements above upon completion of their Bachelor degree. A completed Bachelor’s degree, with appropriate GPA, is required to remain enrolled after admission. Final transcripts of the completed Bachelor degree need to be submitted before students will be allowed to register for classes.
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
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 prerequisite courses. A 3-unit equivalent course in math and in statistics with a grade of B or better can apply for a waiver of the DAT5005 prerequisite course. A 3-unit equivalent course in programming (e.g., C++, C# or Python) with a grade of B or better can apply for a waiver of the DAT5000 prerequisite course.
Applications for a waiver are to be made to the program academic advisor and applicants will be required to take an online test in the requested waiver area - in statistics or in basic programming as applicable - and score 60% or better in order to waive any of the two prerequisite courses.
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 7 years can waive the applicable subject area prerequisite course for the MSDA program. If the masters level courses were completed more than 7 years ago, the waiver applicants will be required to take an online test in the requested waiver area - in statistics or in basic programming as applicable - and score 60% or better in order to waive any of the two prerequisite courses.
The prerequisite courses for this program are to be completed during Session 1 and 2 of Year One:
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