MS in Accounting
Northeastern University in Boston offers a robust MS in Accounting pro...
MS in Data Science Align
Boston
INTAKE: Jan & Sept
Program Overview
Northeastern University’s MS in Data Science Align program is specifically designed for students with non-technical backgrounds who want to transition into the rapidly growing field of data science. This program offers a comprehensive pathway for individuals who may not have a strong foundation in computer science or mathematics, providing them with the core skills necessary to excel in data science roles. Students are introduced to fundamental programming, statistics, and data analysis techniques, before progressing to more advanced topics in machine learning, data engineering, and big data analytics. The Align program is unique in that it caters to individuals seeking to make a career change, offering a robust educational experience along with real-world application through Northeastern's experiential learning opportunities.
Curriculum: The MS in Data Science Align program offers a carefully structured curriculum that begins with foundational courses in programming, statistics, and data analysis. Students learn essential tools and languages, including Python, R, and SQL, which are critical for data manipulation and analysis. As students advance, they take specialized courses in machine learning, data visualization, and artificial intelligence, gaining a deeper understanding of how data science is applied across various industries. The curriculum also includes hands-on projects, case studies, and opportunities to work on real-world problems, ensuring students graduate with practical experience. The program’s flexibility allows students to take courses at a pace that suits their prior knowledge and career goals, making it ideal for those coming from non-technical backgrounds.
Research Focus: The MS in Data Science Align program at Northeastern emphasizes the importance of research in driving innovation in the field of data science. Research areas include machine learning, data privacy, artificial intelligence, big data analytics, and predictive modeling. Students have the opportunity to participate in cutting-edge research through Northeastern’s specialized research labs and institutes, such as the Institute for Experiential AI. The program encourages students to explore interdisciplinary research, applying data science techniques to solve real-world problems in fields such as healthcare, finance, and environmental sustainability. This hands-on research experience prepares students to contribute to the rapidly evolving field of data science.
Industry Engagement: One of the hallmark features of the MS in Data Science Align program is its strong emphasis on industry engagement through Northeastern’s renowned co-op program. Students have the opportunity to work full-time with leading companies in sectors like technology, healthcare, finance, and government, gaining invaluable real-world experience. These co-op placements allow students to apply their learning to solve practical data challenges, while also building their professional networks. In addition to co-ops, the program offers industry-sponsored projects, internships, and collaboration opportunities that connect students with employers and professionals in the field, ensuring they are well-prepared for careers upon graduation.
Global Perspective: The MS in Data Science Align program at Northeastern University incorporates a global perspective by addressing the universal challenges of data science, such as data security, privacy, and analytics across different industries. Students are exposed to global data policies, standards, and ethical considerations, preparing them to navigate the complex regulatory environments faced by international organizations. The program’s diverse student body, which includes individuals from various cultural and professional backgrounds, offers an enriching learning experience and fosters global collaboration. This international outlook ensures that graduates are equipped to tackle data science challenges in any global context, whether in multinational corporations or international research projects.
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 the MS in Data Science Align program at Northeastern University have access to a wide range of career opportunities in the booming field of data science. The program’s interdisciplinary curriculum and hands-on learning approach ensure that students are well-prepared for roles in various industries, including technology, healthcare, finance, and consulting.
Data Scientist: Responsible for analyzing complex datasets to derive actionable insights, develop predictive models, and improve business strategies using machine learning and statistical methods.
Machine Learning Engineer: Specializes in designing and deploying machine learning models and algorithms to solve complex problems, optimize processes, and enhance decision-making in industries such as tech, finance, and e-commerce.
Data Analyst: Focuses on collecting, processing, and analyzing data to help businesses understand trends and patterns, often using tools like SQL, Python, and data visualization platforms such as Tableau.
Business Intelligence Analyst: Uses data analytics to identify business trends, opportunities, and strategies, and provides actionable insights that help organizations make data-driven decisions and improve performance.
AI Engineer: Designs and develops artificial intelligence systems, focusing on machine learning, deep learning, and natural language processing (NLP) to automate processes and improve business efficiency.
Data Engineer: Develops the infrastructure and architecture required to manage and store large datasets, ensuring that data scientists and analysts have access to clean and well-organized data for analysis.
Big Data Architect: Works on building and managing large-scale data systems and architectures that can handle large volumes of structured and unstructured data, ensuring optimal performance, scalability, and security.
Quantitative Analyst: Uses advanced mathematical models and statistical techniques to analyze financial data, assess risk, and optimize trading strategies in industries like finance and investment.
Product Analyst: Works with product teams to analyze customer behavior, usage data, and product performance, providing insights that drive product development and improvement.
Healthcare Data Scientist: Specializes in analyzing healthcare-related data to improve patient care, optimize hospital operations, and contribute to public health research using data science techniques.
