MS in Accounting
Northeastern University in Boston offers a robust MS in Accounting pro...
MS in Data Analytics Engineering
Boston
INTAKE: Jan & Sept
Program Overview
Northeastern University’s MS in Data Analytics Engineering program is designed for students interested in gaining advanced skills in data engineering and analytics. This program provides students with a comprehensive foundation in managing and analyzing large datasets, utilizing cutting-edge technologies and methodologies to extract valuable insights. The curriculum combines data science, engineering, and computational techniques to address complex data challenges in various industries. This interdisciplinary program is ideal for students with a technical background who aim to develop expertise in both the engineering and analytical aspects of data.
Curriculum: The MS in Data Analytics Engineering program at Northeastern offers a rigorous and practical curriculum that covers a wide range of topics essential to data engineering. Students are introduced to core subjects such as database management, big data technologies, machine learning, and data visualization. The program emphasizes the development of technical skills required for data infrastructure, data mining, and cloud computing, while also focusing on how to apply these skills to real-world data challenges. The coursework is structured to ensure that students are well-equipped to handle the complexities of modern data environments, with opportunities for hands-on learning and project-based experience.
Research Focus: Northeastern University places a significant emphasis on research in its MS in Data Analytics Engineering program. Students have the opportunity to engage in cutting-edge research in areas such as predictive analytics, data mining, machine learning, and artificial intelligence. The program encourages students to work on interdisciplinary projects that blend data analytics with other fields like business, healthcare, and social sciences. Research initiatives often take place in Northeastern's renowned labs and institutes, such as the Institute for Experiential AI and the Data Science and Artificial Intelligence Lab, enabling students to contribute to pioneering advancements in the data analytics field.
Industry Engagement: Northeastern University’s strong industry connections are a hallmark of the MS in Data Analytics Engineering program. The university’s cooperative education (co-op) program provides students with the opportunity to work full-time in data-related roles while still pursuing their studies. These partnerships with leading companies in tech, finance, healthcare, and other sectors ensure that students gain valuable real-world experience and build a robust professional network. Students also have access to industry-sponsored projects, allowing them to apply classroom knowledge to solve practical business challenges, further bridging the gap between theory and practice.
Global Perspective: The MS in Data Analytics Engineering program at Northeastern offers a global perspective on data analytics, preparing students to tackle data challenges that transcend national borders. The program incorporates international case studies and perspectives, highlighting how data analytics can be applied to diverse contexts across the world. Students also engage with classmates and faculty from different cultural backgrounds, providing insights into the global nature of data-related issues. This international focus ensures that graduates are prepared to work in global markets and understand how data analytics impacts industries around the world.
Location
Boston
Score
IELTS 6.5
Tuition Fee
USD 29824
Postgraduate Entry Requirements
Academic Qualifications: Applicants for postgraduate programs typically require a minimum academic achievement of 70% or above in their bachelor's degree.
English Language Proficiency:
- IELTS: Overall band score of 6.5 with a minimum of 6.0 in each component.
- TOEFL: Overall score of 79 or higher.
- PTE: Overall score of 53 or higher.
- DET (Duolingo English Test): Minimum score of 105.
Northeastern University in Boston offers a range of scholarship opportunities for international students to help alleviate the financial burden of studying in the United States. These scholarships are designed to support academically talented students from around the world, promoting diversity and fostering an inclusive campus environment.
Merit-Based Scholarships: Northeastern University provides merit-based scholarships to international students based on academic excellence and achievements. These scholarships are awarded during the admissions process and are highly competitive. The amount and criteria for these scholarships may vary, but they aim to recognize students who demonstrate exceptional academic performance, leadership potential, and a strong their chosen field of study.
Northeastern International Scholars Program: This prestigious program offers scholarships to outstanding international students who exhibit leadership, academic excellence, and a desire to contribute to the global community. The Northeastern International Scholars Program provides both financial support and opportunities for personal growth through networking events, leadership training, and involvement in community service initiatives.
Need-Based Financial Aid: Although Northeastern University does not offer need-based financial aid to international students, there are still many merit-based scholarships available that can significantly reduce tuition costs. However, international students are encouraged to seek external scholarships or funding from their home country to help cover the remaining costs.
External Scholarships and Funding: In addition to institutional scholarships, international students at Northeastern University can explore a variety of external scholarship opportunities from governments, foundations, and organizations in their home countries. Many international students receive funding from these sources to support their education at Northeastern.
Graduates of Northeastern University's MS in Data Analytics Engineering program are well-equipped for a wide range of career paths in the growing field of data analytics. The program’s focus on both technical skills and practical experience prepares students for roles in various industries, including technology, finance, healthcare, and government.
Data Engineer: Design, build, and maintain scalable data pipelines, ensuring the efficient flow of data across systems and supporting analytical processes.
Data Scientist: Apply statistical models, machine learning algorithms, and advanced analytics to extract insights from complex datasets and drive data-driven decision-making.
Machine Learning Engineer: Develop and deploy machine learning models that can automate processes, predict trends, and enhance decision-making within organizations.
Business Intelligence Analyst: Analyze data to provide actionable insights that help organizations optimize operations, identify trends, and improve performance.
Big Data Architect: Design and implement the architecture needed to store, process, and analyze large volumes of data efficiently, often working with cloud-based technologies.
Quantitative Analyst (Quant): Use advanced statistical and mathematical models to analyze financial markets, often in sectors such as banking, investment, and insurance.
Data Analytics Consultant: Advise organizations on how to leverage data analytics to solve business problems, improve performance, and optimize strategy.
AI/Deep Learning Engineer: Specialize in developing deep learning models and algorithms that enable systems to mimic human intelligence, focusing on natural language processing, computer vision, and other advanced AI applications.
