MS in Accounting
Northeastern University in Boston offers a robust MS in Accounting pro...
MS in Data Science
Boston
INTAKE: Jan & Sept
Program Overview
Northeastern University’s MS in Data Science program is designed to equip students with the necessary skills to analyze, interpret, and leverage large datasets to drive decision-making across industries. The program provides a rigorous, interdisciplinary curriculum that blends statistics, machine learning, data visualization, and computer science. Students gain expertise in extracting insights from complex data, using tools and techniques that are essential in today’s data-driven world. Northeastern’s emphasis on experiential learning ensures that students have practical, hands-on experience in real-world data science challenges, preparing them for careers in sectors such as technology, healthcare, finance, and business.
Curriculum: The MS in Data Science curriculum at Northeastern University focuses on a blend of theoretical knowledge and applied skills. Core courses include statistical analysis, machine learning, data visualization, and data mining, with an emphasis on the practical use of programming languages such as Python and R. The program also incorporates advanced topics such as artificial intelligence, deep learning, and natural language processing, ensuring that students are prepared for the latest challenges in the field. Additionally, students can choose from a range of electives in areas like data engineering, computational biology, and business analytics, allowing them to tailor their education to specific career goals.
Research Focus: Northeastern University’s MS in Data Science program offers students the opportunity to engage in cutting-edge research in various areas of data science. Research initiatives focus on critical areas such as machine learning, big data analytics, artificial intelligence, and the ethical implications of data. Students collaborate with faculty members on research projects that seek to solve real-world problems, from improving healthcare outcomes to optimizing business operations. Northeastern's research centers, including the Institute for Experiential AI, provide students with access to state-of-the-art facilities and projects that push the boundaries of data science and its applications.
Industry Engagement: Northeastern University’s MS in Data Science program is known for its strong industry connections and emphasis on experiential learning. The university’s cooperative education (co-op) program offers students the chance to work full-time with leading companies in technology, finance, healthcare, and other industries while completing their studies. This hands-on experience allows students to apply classroom knowledge to solve real-world problems, gain insights into industry practices, and build valuable professional networks. In addition to co-ops, the program includes industry-sponsored projects and internships, which further enhance students' job readiness upon graduation.
Global Perspective: The MS in Data Science program at Northeastern University incorporates a global perspective, preparing students to address data science challenges in a variety of international contexts. The program includes coursework and case studies that highlight the global impact of data-driven decision-making in fields like healthcare, environmental science, and economics. Furthermore, students interact with classmates and faculty from diverse cultural backgrounds, broadening their understanding of how data science is applied across different industries and regions. This global outlook ensures that graduates are prepared to work in international markets and collaborate with global teams to solve complex data problems.
Location
Boston
Score
IELTS 6.5
Tuition Fee
USD 29696
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 Science program are equipped with the skills and knowledge to pursue a wide range of careers in the data science and analytics fields. The program’s interdisciplinary approach, which combines machine learning, data analysis, and statistics with practical experience, ensures that students are well-prepared for roles across various industries, including technology, healthcare, finance, and government.
Data Scientist: Use advanced statistical and machine learning techniques to analyze and interpret large datasets, deriving actionable insights to guide business strategies and decisions.
Machine Learning Engineer: Focus on developing algorithms and predictive models that can automate processes, improve decision-making, and enhance operational efficiency.
Data Analyst: Analyze and interpret data to help organizations make informed decisions, using tools like SQL, R, Python, and data visualization software to identify trends and insights.
Business Intelligence Analyst: Use data analytics to support business operations by identifying key trends, forecasting future outcomes, and providing strategic insights that help businesses stay competitive.
Quantitative Analyst: Apply advanced mathematical models and statistical techniques to solve complex problems in fields such as finance, investment, or risk management.
AI Specialist: Design and implement artificial intelligence solutions to solve complex problems, including natural language processing, computer vision, and autonomous systems.
Data Engineer: Build and maintain the infrastructure and systems necessary for collecting, storing, and processing large volumes of data, enabling data scientists and analysts to work efficiently.
Big Data Architect: Design and manage big data systems and architectures that can handle vast amounts of structured and unstructured data, ensuring scalability, security, and performance.
Data Science Consultant: Advise businesses and organizations on how to leverage data to optimize operations, reduce costs, and enhance overall performance, often by developing customized data strategies.
Healthcare Data Analyst: Analyze healthcare-related data to improve patient outcomes, optimize hospital management, and support clinical decision-making with data-driven insights.
