Master of Accounting
The Master of Accounting program at Monash University offers a compreh...
Bachelor of Applied Data Science (Advanced)
Melbourne
INTAKE: February
Program Overview
Monash University's Bachelor of Applied Data Science (Advanced) program is designed for students seeking a deeper understanding and specialized skills in the field of data science. It combines foundational knowledge in statistics, computer science, and mathematics with advanced coursework in machine learning, big data analytics, and data visualization. The program emphasizes hands-on experience through industry placements, research projects, and practical training, preparing students for leadership roles in data-driven industries.
Curriculum: The curriculum of the Bachelor of Applied Data Science (Advanced) program at Monash University is rigorous and interdisciplinary. It includes core courses in data mining, predictive modeling, artificial intelligence, and cloud computing, complemented by elective options in specialized areas such as natural language processing, deep learning, and cybersecurity. Students engage in capstone projects and have opportunities to collaborate with industry partners on real-world challenges, enhancing their analytical and problem-solving skills.
Research Focus: Monash University is at the forefront of data science research, with faculty members and research centers conducting innovative studies in areas such as data ethics, computational biology, social analytics, and urban informatics. The Bachelor of Applied Data Science (Advanced) program integrates research principles into the curriculum, encouraging students to explore cutting-edge techniques and contribute to ongoing research projects. Students can participate in research internships and work alongside leading academics to address global challenges through data-driven innovation.
Industry Engagement: Monash University maintains strong connections with industry partners across sectors including finance, healthcare, technology, and government. The Bachelor of Applied Data Science (Advanced) program emphasizes industry engagement through internships, guest lectures, and collaborative projects. Students gain practical experience and industry insights, learning to apply theoretical knowledge to real-world scenarios. These partnerships also facilitate networking opportunities and enhance students' employability upon graduation.
Global Perspective: With campuses in Australia, Malaysia, and South Africa, Monash University offers a truly global perspective to students in the Bachelor of Applied Data Science (Advanced) program. The curriculum incorporates international case studies, cross-cultural collaboration opportunities, and exchange programs that allow students to broaden their academic and cultural horizons. Graduates are prepared to work in diverse global settings, equipped with the skills and understanding needed to navigate the complexities of a data-driven world.
Location
Melbourne
Score
IELTS 6.5
Tuition Fee
AUD 50200
Undergraduate Entry Requirements
Application Fee: AUD $100
Academic Qualifications: Applicants for undergraduate programs typically require a minimum academic achievement of 70% or above in their previous academic qualifications.
English Language Proficiency:
- IELTS: Overall band score of 6.0 or 6.5 with a minimum of 5.5 in each component.
- TOEFL: Overall score of 80 with a minimum of 19 in each section.
- PTE (Pearson Test of English): Overall score of 58 with a minimum of 50 in each section.
Students must provide:
- academic marksheets & transcripts
- letters of recommendation
- a personal statement - SOP
- passport
- other supporting documents as required by the university.
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.
Monash University offers a range of scholarships to both domestic and international students to help cover the cost of tuition fees, living expenses, and other study-related costs. These scholarships are awarded based on academic excellence, financial need, leadership potential, and other criteria.
Monash International Merit Scholarship: This scholarship is offered to international students who have demonstrated academic excellence in their previous studies. The scholarship provides up to $10,000 per annum for the duration of the student's course.
Monash Asylum Seekers Scholarship: This scholarship is designed to provide financial assistance to asylum seekers who are undertaking undergraduate or postgraduate study at Monash University. The scholarship covers the cost of tuition fees, as well as a range of other study-related expenses.
Monash Equity Scholarship: This scholarship is offered to students who have experienced financial hardship or other forms of disadvantage that have impacted their ability to succeed academically. The scholarship provides up to $6,000 per annum to assist with living expenses and other costs.
Monash Indigenous Scholarship: This scholarship is available to Indigenous students who are undertaking undergraduate or postgraduate study at Monash University. The scholarship provides a range of benefits, including financial assistance, mentoring, and academic support.
Graduates of Monash University's Bachelor of Applied Data Science (Advanced) program are well-equipped with advanced skills in data science, making them highly sought after across various industries. The program prepares students for a wide range of rewarding career opportunities where data-driven decision-making and advanced analytics are paramount.
Data Scientist: Data scientists are in high demand across industries for their expertise in analyzing large datasets, building predictive models, and extracting valuable insights. They utilize advanced statistical and machine learning techniques to solve complex problems and drive business decisions.
Machine Learning Engineer: Machine learning engineers specialize in designing, implementing, and optimizing machine learning algorithms and models. They collaborate with data scientists and software developers to deploy scalable solutions for automated data analysis, pattern recognition, and decision-making systems.
Data Engineer: Data engineers focus on designing and constructing data pipelines and infrastructure to ensure data availability, reliability, and scalability. They work with big data technologies and cloud platforms to manage and process large volumes of data efficiently.
Business Intelligence Analyst: Business intelligence analysts leverage data visualization tools and techniques to transform raw data into actionable insights for organizational stakeholders. They create dashboards and reports that facilitate strategic decision-making and performance monitoring across departments.
Data Architect: Data architects design and oversee the implementation of data management solutions that support organizational goals. They develop data models, define data governance frameworks, and ensure data security and integrity throughout the data lifecycle.
Research Scientist: Research scientists pursue careers in academia, research institutions, or industry, conducting advanced research in data science, artificial intelligence, and related fields. They contribute to scientific advancements through experimental design, data analysis, and publication of findings.
Consultant/Advisor: Data science consultants provide strategic guidance to businesses on implementing data-driven strategies and solutions. They offer expertise in data strategy development, analytics implementation, and optimization of business processes to achieve competitive advantage.
Financial Analyst: Financial analysts use quantitative analysis and modeling techniques to evaluate investment opportunities, assess risk, and forecast market trends. They leverage data analytics to support decision-making in finance, investment banking, and financial planning.
Healthcare Data Analyst: Healthcare data analysts apply data science methods to healthcare data sets to improve patient care, optimize hospital operations, and support medical research. They collaborate with healthcare professionals to implement data-driven solutions that enhance healthcare delivery and outcomes.
