软件工程硕士

这个为期15个月，为期5个季度的计划从秋季开始，通过动手编程使学生接触到计算机的广泛主题，然后提供专门的软件工程课程，涵盖如何设计现有软件以及该领域的基本原理。该计划将指导学生在软件的设计，实施，测试和维护方面进行广泛的实践，并为专业职业的非技术方面做好准备。在最后一个秋季季度进行的暑期实习和顶峰项目使学生可以练习在课堂上学到的技能，并品尝一下该领域的期望。该计划中嵌入的专业发展课程为学生做好了面试的准备，并帮助他们发展职业技能，以确保毕业后能找到一份工作。所有领域的大型公司和小型初创公司都需要软件工程师
The Master of Software Engineering (MSWE) is a professionally oriented, programming-intensive, degree program designed to train students from a variety of backgrounds for Software Engineering careers. To be eligible, applicants must have a bachelor's degree (or equivalent), and be proficient in two programming languages.<br>The program's characteristics are as follows:<br>A 15-month, 49.3-unit, on-campus program, spanning from September of the first year to December of the second year.<br>Dedicated study room in which MSWE students are encouraged to study and work on their projects.<br>First quarter of intensive programming exercises designed to solidify and broaden students knowledge of the large computing landscape, covering essential knowledge in Computer Science and Computer Systems.<br>Students will spend close to 1,300 hours learning through programming and analyzing code.<br>Domestic professionals working full-time must enroll in the MSWE program part-time. All other students must enroll full-time.<br>The Career Development Team offers group workshops and 1-on-1 appointments to guide students on all aspects of securing an internship and full-time position, such as resume review and salary negotiation.<br>The MSWE curriculum includes:<br><br>Six courses that cover the foundations of software construction, maintenance, and quality, via hands-on projects.<br>Courses that help prepare students for the non-technical aspects of professional careers.<br>An experiential learning requirement, in which students are responsible for securing an internship or project during the summer. <br>A small-group capstone project during the final quarter, in which students will be responsible for designing and implementing a substantial piece of software, be it standalone or an add-on to an existing system. This project includes challenging aspects, such as information classification and machine learning modules, strict performance requirements, very large code bases, deployment in the cloud, etc.