The Master of Science, MS, degree in Software Engineering Systems (formerly Computer Systems Engineering) approaches software development from the analytical and methodological perspective of an engineer. Youll build advanced design and engineering skills, enhance knowledge in cloud computing, and develop machine learning algorithms. With your passion for high-performance technology, large-scale machine learning, and AI-type algorithms, youll become an intuitive problem solver, experienced engineering architect, and results-focused leader. Your knowledge of the three-way intersection of computer science, engineering, and ethics will enable you to have real-world societal impact in a high-demand field across industries.<br>At Northeastern, you have flexibility to select from coursework-only or thesis-based options, gain professional experience on co-op, work on real-world projects, and learn the latest technologies from industry-leading faculty.<br>Our master's in software engineering systems program offers a multitude of courses in big-data engineering and analytics in addition to supplementary courses with the intention to deliver data-analytics results in a meaningful way to management.<br>The program covers data management, advanced data management, business intelligence, column databases, data science, and big-data engineering. Advanced functional programming using the powerful Scala language and a course on advanced data science as well as cloud computing is offered. Multi-thread concurrent computing is also offered as it is important for synchronizing a huge set of servers working in parallel to do large-scale analytics to make things run faster by a hundredfold increase in speed. Due to the high-level mathematical operations required to run these programs, only software engineers have the capacity to work in such complicated areas. Only they can make the necessary mathematical algorithms execute quickly enough to get the finest results.Our engineers become fluent in data science with the intention of building the actual system. They study how to write machine-learning algorithms on top of statistical packages.