M.S. in Systems Engineering
The M.S. in Systems Engineering program at Johns Hopkins University is designed for ind...
M.S.E. in Data Science
Baltimore, Maryland
INTAKE: Jan & Aug
Program Overview
The M.S.E. in Data Science program at Johns Hopkins University is designed to prepare students for careers in the rapidly growing field of data science. The program focuses on the interdisciplinary nature of data science, combining elements of computer science, statistics, and domain-specific knowledge. Students learn to apply statistical and computational techniques to analyze data, derive meaningful insights, and make informed decisions.
Curriculum:
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Core Courses: The program begins with core courses that provide a solid foundation in data science principles. These courses cover topics such as data mining, machine learning, statistical analysis, data visualization, and big data analytics. Students gain a comprehensive understanding of the key concepts and methodologies used in data science.
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Statistical Analysis and Modeling: The curriculum emphasizes statistical analysis and modeling techniques, equipping students with the skills to extract meaningful insights from data. Students learn to apply statistical methods, design experiments, and build predictive models to solve real-world problems.
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Machine Learning and Data Mining: The program covers advanced topics in machine learning and data mining, enabling students to develop algorithms and models that can automatically learn and make predictions from data. Students learn techniques such as supervised and unsupervised learning, deep learning, and natural language processing.
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Data Visualization: Effective data visualization is essential for communicating insights and findings. The program includes coursework on data visualization, teaching students how to create visually compelling representations of data and use interactive tools for exploration and analysis.
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Big Data Analytics: With the increasing volume and complexity of data, the program addresses the challenges of big data analytics. Students learn techniques for handling large datasets, distributed computing, and scalable data processing frameworks.
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Elective Courses: The program offers a variety of elective courses that allow students to specialize in areas of interest within data science. Elective options may include topics such as text mining, social network analysis, time series analysis, or healthcare analytics. Students can tailor their curriculum to align with their career goals and research interests.
Location
Baltimore, Maryland
Score
IELTS : 7
Tuition Fee
USD 58720
Johns Hopkins University has specific entry requirements for international students seeking admission to their postgraduate programs.
Application Fees : US$ 75
Postgraduate Programs
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Academic Qualifications: International students applying for postgraduate programs at Johns Hopkins University are expected to have completed their previous education with a minimum academic performance of 70% or above. This requirement ensures that applicants have a strong academic foundation to succeed in their chosen field of study.
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English Language Proficiency: For postgraduate programs, a minimum IELTS score of 7 or a minimum TOEFL score of 100 is typically required.
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Graduate Record Examination (GRE): For postgraduate programs, a competitive GRE score of around 313 is generally expected.
However, it is important to note that specific program requirements may vary, and students should check the requirements for their intended program of study.
Johns Hopkins University recognizes the importance of providing financial support to international students to make their education more accessible. The university offers a range of scholarships and financial aid opportunities specifically for international students.
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Global Scholarships: Johns Hopkins University offers a limited number of merit-based scholarships to exceptional international students. These scholarships are highly competitive and are awarded based on academic achievements, leadership potential, and other outstanding qualities. The Global Scholarships can cover full or partial tuition costs.
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Need-Based Financial Aid: The university also provides need-based financial aid to international students who demonstrate financial need. Through the Office of Financial Aid, students can apply for grants, loans, and work-study opportunities to help cover their educational expenses.
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External Scholarships: Johns Hopkins University encourages international students to explore external scholarship opportunities. The university maintains a list of external scholarship programs and resources that students can access to fund their education. These scholarships may be provided by government organizations, private foundations, or other institutions.
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Departmental Scholarships: Some academic departments within the university offer scholarships and assistantships specifically for international students pursuing certain fields of study. These scholarships are often based on academic excellence and may provide financial support for tuition fees and living expenses.
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Diversity and Inclusion Scholarships: Johns Hopkins University is committed to promoting diversity and inclusion within its student body. As part of this commitment, the university offers scholarships and grants to students from underrepresented backgrounds, including international students, who contribute to the diversity and inclusive culture of the university.
It's important to note that the availability and eligibility criteria for scholarships may vary each year.
Graduates of the M.S.E. in Data Science program at Johns Hopkins University have excellent career prospects in a wide range of industries.
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Data Scientist: Graduates are well-equipped for data scientist roles, where they apply their expertise in data analysis, statistical modeling, and machine learning to derive insights and solve complex problems. They work with large datasets to extract actionable information and make data-driven decisions.
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Data Analyst: Graduates can work as data analysts, focusing on data exploration, visualization, and reporting. They analyze data to identify trends, patterns, and correlations, providing valuable insights to support business strategies and decision-making.
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Machine Learning Engineer: With their advanced knowledge of machine learning algorithms and techniques, graduates can work as machine learning engineers, developing and implementing models and algorithms that enable machines to learn and make predictions.
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Data Engineer: Graduates can pursue careers as data engineers, responsible for designing and maintaining data infrastructure and systems. They develop data pipelines, ensure data quality and integrity, and optimize data storage and retrieval processes.
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Business Intelligence Analyst: Graduates can work as business intelligence analysts, utilizing their data analysis skills to provide insights and support strategic decision-making within organizations. They use data visualization techniques to communicate complex findings to stakeholders.
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Research Scientist: Graduates can pursue research positions in academia, industry, or government organizations. They contribute to advancements in data science by conducting research, developing new algorithms or methodologies, and publishing their findings in academic journals or conferences.
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Data Consultant: Graduates can work as data consultants, providing expertise and guidance to organizations seeking to leverage data for strategic decision-making. They help companies optimize their data analytics processes, implement data-driven strategies, and solve complex data-related challenges.
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Entrepreneurship: Some graduates may choose to start their own data-driven ventures and become entrepreneurs. They can leverage their knowledge of data science and analytics to develop innovative products or services, addressing industry-specific challenges or gaps.
