Master of Architecture
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Melbourne City
INTAKE: Jul & Feb
RMIT University's Master of Data Science program offers a comprehensive and contemporary education in the field of data analytics. The program encompasses a wide range of topics, including data mining, machine learning, statistical analysis, and data ethics. Students acquire a strong foundation in data processing, enabling them to work with large and complex datasets.
Curriculum: The program's curriculum is thoughtfully structured to provide students with a solid grounding in data science. Courses cover areas such as data visualization, predictive modeling, and big data analytics. Students gain practical experience by working with real-world data and using industry-standard tools and software for data analysis.
Research Focus: The Master of Data Science program emphasizes research and innovation, allowing students to explore advanced topics in data analytics. Students have the opportunity to engage in research projects focused on artificial intelligence, data security, and data-driven decision-making. Collaboration with faculty and industry partners on research initiatives empowers students to contribute to the development of data science knowledge.
Industry Engagement: RMIT University maintains strong connections with industry partners, ensuring students gain exposure to real-world data analytics challenges and solutions. The program often includes guest lectures by industry experts, internships with leading organizations, and collaborative data projects. These industry engagements provide students with valuable practical experience and networking opportunities.
Global Perspective: The Master of Data Science program at RMIT University promotes a global perspective, addressing international trends in data analytics, cross-cultural data challenges, and the influence of globalization on data-driven decision-making. RMIT's diverse and inclusive learning environment, with a global student body, enhances the international perspective of the program.
Melbourne City
IELTS 6.5
AUD 38400
Postgraduate Entry Requirements:
Academic Qualifications: Typically, a minimum of 60% or above in your previous academic qualifications is required for postgraduate programs.
English Language Proficiency:
Students must provide:
Work experience: Some postgraduate courses may require relevant work experience in the field.
It's important to note that entry requirements can vary by program and may change over time. Additionally, some programs may have additional requirements, such as interviews, portfolios, or work experience.
RMIT University offers a range of scholarships to international students to support their educational journey. These scholarships are designed to recognize academic excellence, leadership potential, and contributions to the community.
Graduates of the Master of Data Science program at RMIT are well-prepared for a multitude of career options in the field of data analytics.
Data Scientist: Graduates can work as data scientists, responsible for extracting insights from data, developing models, and making data-driven decisions.
Machine Learning Engineer: Those interested in machine learning can become machine learning engineers, designing and implementing machine learning solutions for predictive analytics.
Business Intelligence Analyst: Graduates may choose to work as business intelligence analysts, focusing on translating data into actionable business insights.
Data Analyst: Graduates can work as data analysts, responsible for collecting, processing, and analyzing data to provide valuable insights to organizations.
Big Data Engineer: Graduates may opt for careers as big data engineers, responsible for managing and processing large volumes of data in big data environments.
Risk Analyst: Graduates can become risk analysts, assessing data-related risks in various industries, including finance and insurance.
Consultant in Data-Driven Decision-Making: Graduates can work as consultants, guiding organizations in implementing data-driven decision-making strategies.