国际学生入学条件
To be eligible for consideration to any graduate program (M.S. or Ph.D.) at NYU Tandon, you must hold a Bachelor's degree from a regionally accredited U.S. institution, or its international equivalent, which includes a minimum of four years of full-time undergraduate study. We do not accept undergraduate degrees that are equivalent to three years of study. However, Bachelor of Engineering degrees that are completed within the Bologna signatory system, and earn 180+ ECTS credits, are eligible for consideration. Please note that the minimum GPA requirement is a 3.0 out of a 4.0 scale. The NYU Tandon School of Engineering requires that graduate applicants achieve a minimum TOEFL score of 90 on the internet-based test, an overall band of 7.0 on IELTS.
展开 IDP—雅思考试联合主办方
雅思考试总分
7.0
了解更多
雅思考试指南
- 雅思总分:7
- 托福网考总分:90
- 托福笔试总分:160
- 其他语言考试:PTE - 65
CRICOS代码:
申请截止日期: 请与IDP顾问联系以获取详细信息。
课程简介
复杂的建模和信息技术现在主导着金融世界。当今,金融理论和实践受到复杂的金融和全球系统以及动态变化的监管环境和政治的挑战。在纽约大学工程学院,我们训练学生做到这一点:设计未来的金融并将金融理论转化为实践。金融工程硕士课程为学生提供有关金融概念的基础知识。这些知识然后成为专业领域的跳板,学生可以在其中应用概念,从衍生品风险金融到金融IT以及大数据上的算法交易。全日制学生将在4个学期内完成课程
Sophisticated modeling and information technology now dominate the financial world. The theories and the practice of Finance are challenged today by complex financial and global systems and by dynamically changing regulatory environments and politics. A global world in transition creates both opportunities and challenges for financial engineers to adapt theoretical and financial constructs into profitable and innovative opportunities by creating innovative, custom-designed instruments in the marketplace.At the NYU School of Engineering, we train our students to do exactly that: to engineer the future of finance and transform financial theory into practice. The MS in Financial Engineering program furnishes students with foundational knowledge in financial concepts. This knowledge then becomes a springboard to specialized fields where students can apply concepts to everything from derivatives risk finance to financial IT and algorithmic trading on Big Data.
展开