Master of Science in Data Analytics Engineering
Funding Early Action deadline (international and domestic) January 15
Deadline for international applicants outside of the U.S.: May 15
Deadline for international applicants inside the U.S.: July 1
Deadline for domestic applicants: August 1
Deadline for regional campus applicants: August 15
The MS in Data Analytics Engineering program offers students an opportunity to train for industry jobs or to acquire rigorous analytical skills and research experience to prepare for a doctoral program in health, security, and sustainability at Northeastern University. The Department of Mechanical and Industrial Engineering offers this degree program in order to meet the current and projected demand for a workforce trained in analytics. While the core courses for this program are offered by the College of Engineering, elective courses can be chosen from diverse disciplines spread across various colleges at Northeastern. The MS degree in data analytics engineering is designed to enable the graduating students to address the growing need for professionals who are trained in advanced data analytics and can transform large streams of data into understandable and actionable information for the purpose of making decisions. The key sectors that require analytics professionals include healthcare, smart manufacturing, supply chain and logistics, national security, defense, banking, finance, marketing, and human resources.
This degree program seeks to prepare students for a comprehensive list of tasks including collecting, storing, processing and analyzing data, reporting statistics and patterns, drawing conclusions and insights, and making actionable recommendations.
- This program meets F-1 international student status requirements.
- Core courses for this program are offered by the College of Engineering, while elective courses can be chosen from diverse disciplines spread across various colleges at Northeastern.
- This program is designed to enable the graduating students to address the growing need for professionals who are trained in advanced data analytics.
The MS in Data Analytics Engineering is designed to help students acquire knowledge and skills to
• Discover opportunities to improve systems, processes, and enterprises through data analytics
• Apply optimization, statistical, and machine-learning methods to solve complex problems involving large data from multiple sources
• Collect and store data from a variety of sources, including internet of things, an integrated network of devices and sensors, customer touch points, processes, social media, and people
• Work with technology teams to design and build large and complex SQL databases
• Use tools and methods for data mining, Big Data algorithms, and data visualization to generate reports for analysis and decision making
• Create integrated views of data collected from multiple sources of an enterprise
• Understand and explain results of data analytics to decision makers
• Design and develop analytics projects
|IE 5374||Special Topics in Industrial Engineering (Data Visualization Engineering)||4|
|IE 6200||Engineering Probability and Statistics||4|
|IE 7275||Data Mining in Engineering||4|
|IE 7280||Statistical Methods in Engineering||4|
|INFO 6210||Data Management and Database Design||4|
|OR 6205||Deterministic Operations Research||4|
Cooperative Education Program (Co-Op)
The College of Engineering Graduate Cooperative Education Program is one option for experiential learning and is available on a competitive basis to selected students. Co-op at the graduate level is not just a way for students to gain real-world experience, but is a way to challenge, network, expand, and fine-tune their knowledge within their respective industry. The goals of co-op are to:
- Apply knowledge and skills in new, authentic contexts.
- Develop new knowledge and skills.
- Integrate and use the deepened knowledge and skills in your academic programs.
- Reflect on and articulate how you used your knowledge and skills, how you gained new knowledge and skills, and how “theory and practice” work together.
The Graduate School of Engineering placed over 800 students with some of the most sought-after technical skills in positions nationally during the 2018 academic year. We have a team that prepares students for co-op experience through resumé building, developing interview skills, and guiding professional development.
For 2019, students admitted to the MS in Data Analytics Engineering program in Seattle are eligible to receive a 25-percent tuition scholarship. The scholarship will save students about $12,000 on their overall tuition. For more information, contact the Graduate School of Engineering at firstname.lastname@example.org.
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