Master of Science in Technology - Quality Management and Analytics (Non Thesis)

学历文凭
Masters Degree

专业院系
质量控制技术

开学时间

课程时长

课程学费

国际学生入学条件
have earned a four-year bachelor's degree or its equivalent from a college or university that is accredited by the appropriate regional accrediting association, or do so within one academic year.
present unofficial transcripts from each college or university other than Illinois State at which graduate, undergraduate, or non-degree credit was earned. The unofficial transcript should be easily readable and clearly indicate degree(s) awarded, courses and course grades for each term.
have a cumulative GPA of 3.25 on a 4.0 scale for either the last 60 hours of undergraduate coursework or any previous work in a master's program.
submit official GRE Scores if GPA is below a 3.0 cumulative or 3.25 on the last 60 hours of undergraduate coursework (use institutional code 1319)
IELTS overall band score: 6.5, TOEFL internet-based (iBT): 79, Duolingo: 105
present unofficial transcripts from each college or university other than Illinois State at which graduate, undergraduate, or non-degree credit was earned. The unofficial transcript should be easily readable and clearly indicate degree(s) awarded, courses and course grades for each term.
have a cumulative GPA of 3.25 on a 4.0 scale for either the last 60 hours of undergraduate coursework or any previous work in a master's program.
submit official GRE Scores if GPA is below a 3.0 cumulative or 3.25 on the last 60 hours of undergraduate coursework (use institutional code 1319)
IELTS overall band score: 6.5, TOEFL internet-based (iBT): 79, Duolingo: 105
IDP—雅思考试联合主办方

雅思考试总分
6.5
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- 雅思总分:6.5
- 托福网考总分:79
- 托福笔试总分:160
- 其他语言考试:Duolingo: 105
CRICOS代码:
申请截止日期:请 与IDP联系 以获取详细信息。
课程简介
The sequence introduces quality management tools to enhance customer and supplier relations, strategic planning, and measurement systems to improve overall organizational performance. Students will learn and apply quantitative analytical modeling techniques to solve decision problems and risk situations faced by project managers. In addition, an overview of six sigma data-driven decision making methodologies will be introduced to gain insights into advanced quality based industrial management techniques.
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