Master of Architecture
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Melbourne City
INTAKE: Jul & Feb
RMIT University's Master of Analytics program offers a comprehensive and practical education in the field of data analytics. The program covers a wide range of topics, including data visualization, predictive modeling, machine learning, and data ethics. Students are provided with a strong foundation in statistics and data management, enabling them to work with large datasets and extract meaningful information.
Curriculum: The curriculum of the program is designed to provide students with a well-rounded education in data analytics. It includes courses on data mining, business intelligence, and data-driven decision-making. Students also gain hands-on experience by working with real-world data and using industry-standard tools and software for data analysis.
Research Focus: The Master of Analytics program places a strong emphasis on research and innovation. Students have the opportunity to engage in research projects related to data analytics, exploring topics such as artificial intelligence, big data, and data security. Collaboration with faculty and industry partners on research initiatives allows students to contribute to the advancement of data analytics knowledge.
Industry Engagement: RMIT University maintains close ties with industry partners, ensuring that 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 projects that address industry-specific problems. These industry engagements provide students with valuable practical experience and networking opportunities.
Global Perspective: The Master of Analytics program at RMIT University fosters a global perspective, addressing international trends in data analytics, cross-cultural data challenges, and the impact of globalization on data-driven decision-making. RMIT's diverse and inclusive learning environment, with a global student body, enhances the global perspective of the program.
Melbourne City
IELTS 6.5
AUD 36480
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 Analytics program at RMIT are well-prepared for a wide range of career options in the field of data analytics.
Data Analyst: Graduates can work as data analysts, responsible for collecting, processing, and analyzing data to provide actionable insights for decision-makers.
Business Intelligence Analyst: Those interested in business analytics can become business intelligence analysts, focusing on translating data into strategic insights.
Data Scientist: Graduates may choose to work as data scientists, developing complex models and algorithms to extract knowledge from data.
Machine Learning Engineer: Graduates can work as machine learning engineers, designing and implementing machine learning solutions for predictive analytics.
Data Engineer: Graduates may opt for careers as data engineers, responsible for data collection, storage, and retrieval in big data environments.
Business Consultant: Graduates can become data-driven business consultants, advising organizations on data strategy and analytics implementation.
Risk Analyst: Graduates can work as risk analysts, evaluating and managing data-related risks in financial and insurance sectors.