Master of Data Science (Data Analytics)

Postgraduate Entry Requirements:

Academic Requirement: A minimum of 60% and above in the relevant qualifying examination, such as a bachelor's degree or equivalent.

English Language Proficiency: 

• IELTS (International English Language Testing System): An overall score of 6.5 or 7.0, with a minimum score of 6 in each individual section.
• TOEFL (Test of English as a Foreign Language): An overall score of 80, with a minimum of 19 in listening, 19 in reading, 23 in writing, and 21 in speaking.
• PTE (Pearson Test of English): An overall score of 50, with a minimum of 50 in each individual section.

Students must provide:

• academic marksheets & transcripts
• letters of recommendation
• a personal statement - SOP
• passport
• other supporting documents as required by the university.

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.

The University of Southern Queensland (USQ) in Australia is deeply making high-quality education accessible to a diverse international student community. To support this commitment, the university offers a range of scholarships tailored to recognize academic achievement, promote diversity, and alleviate financial burdens for international students.

1. Academic Excellence Scholarships: USQ values and rewards exceptional academic performance. International students who have demonstrated outstanding scholarly achievements may be eligible for academic excellence scholarships. These scholarships are often based on factors such as grade point averages (GPA) or standardized test scores.
2. Diversity Scholarships: The university values diversity and believes in providing equal opportunities to students from various backgrounds and regions. Diversity scholarships are designed to support students from underrepresented areas or cultural groups, fostering inclusivity within the international student body.
3. Financial Need-Based Scholarships: Recognizing that financial constraints can be a significant barrier to education, USQ offers need-based scholarships to support students with limited financial resources. These scholarships aim to alleviate the financial burden of tuition and living expenses.
4. Leadership and Extracurricular Scholarships: The university encourages students to engage in leadership roles and participate in extracurricular activities. International students who have demonstrated exceptional leadership skills and active involvement in extracurricular activities may qualify for these scholarships.
5. Country-Specific Scholarships: USQ may offer scholarships tailored to specific countries or regions, aiming to attract students from particular areas and promote cross-cultural understanding.

Master of Data Science (Data Analytics): Graduates of the program have a multitude of career options in the field of data analytics.

1. Data Analyst: Data analysts are responsible for collecting, processing, and analyzing data to extract valuable insights that inform business decisions.

2. Business Intelligence Analyst: Business intelligence analysts use data analytics to provide insights for business strategy and decision-making, often by creating data visualizations and reports.

3. Data Scientist: Data scientists employ advanced data analytics techniques, including machine learning and predictive modeling, to solve complex business problems.

4. Quantitative Analyst (Quant): Quants use data analytics to analyze financial data and develop quantitative models for financial markets and risk management.

5. Market Research Analyst: Market research analysts gather and analyze data on consumer preferences and market trends to help businesses make informed decisions.

6. Statistical Analyst: Statistical analysts focus on statistical data analysis to draw meaningful conclusions and provide recommendations.

7. Healthcare Data Analyst: Healthcare data analysts work in the healthcare industry to analyze medical data, patient outcomes, and health trends.

8. Data Visualization Specialist: Data visualization specialists create visual representations of data to help organizations understand complex information.

9. Predictive Modeler: Predictive modelers develop models that predict future outcomes based on historical data, which is valuable for various industries.

10. Data Consultant: Data consultants provide expert advice to organizations on data analysis and strategy, helping them derive insights from their data.