Bachelor of Data Science

Undergraduate Entry Requirements

Academic Qualifications: Applicants for undergraduate programs typically require a minimum academic achievement of 65% or above in their previous academic qualifications.

English Language Proficiency:

• IELTS: Overall band score of 6.0 or 6.5 with a minimum of 6.0 in each component.
• TOEFL: Overall score of 79 with a minimum of 21 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.

Queensland University of Technology (QUT) is fostering a diverse and inclusive learning environment, and one of the ways it achieves this is by offering a range of scholarships to international students. These scholarships are designed to recognize academic excellence, support financial needs, and encourage students to pursue their educational goals at QUT. 

QUT Excellence Scholarship: This prestigious scholarship is awarded to high-achieving international students who demonstrate outstanding academic performance. It provides financial support for tuition fees and offers a unique opportunity to be part of the QUT College of Excellence.

QUT International Merit Scholarship: This scholarship is available to international students who excel academically. It offers a partial tuition fee waiver to help reduce the cost of studying at QUT, making it a more affordable option for deserving students.

Government Scholarships: QUT collaborates with various governments and organizations to provide additional scholarship opportunities to international students. These scholarships may cover a wide range of disciplines and levels of study, making them accessible to a diverse group of students.

External Scholarships: QUT encourages international students to explore external scholarship opportunities that may be available through government agencies, private organizations, and foundations. The university provides guidance and support in identifying and applying for these scholarships.

Graduates of the Bachelor of Data Science program at Queensland University of Technology (QUT) are well-equipped with a diverse skill set that prepares them for dynamic careers in the rapidly growing field of data science. This program integrates computer science, statistics, and domain expertise to analyze large datasets and extract valuable insights, making graduates highly sought after in various industries. 

Data Analyst: Data analysts interpret and analyze data to identify trends, patterns, and relationships that can inform business decisions. They work in industries such as finance, healthcare, marketing, and retail, using statistical tools and programming languages to extract actionable insights from large datasets.

Data Scientist: Data scientists use advanced statistical and machine learning techniques to develop predictive models and algorithms. They work on complex problems such as recommendation systems, fraud detection, and predictive analytics, helping organizations leverage data to improve decision-making and operational efficiency.

Machine Learning Engineer: Machine learning engineers design, implement, and optimize machine learning models and algorithms. They work closely with data scientists and software engineers to deploy models into production systems, ensuring scalability, reliability, and performance.

Business Intelligence Analyst: Business intelligence analysts focus on analyzing organizational data to provide insights into business performance and strategy. They use data visualization tools and dashboards to present data-driven recommendations to stakeholders and support strategic decision-making processes.

Data Engineer: Data engineers are responsible for designing and building data pipelines and infrastructure. They ensure the efficient collection, storage, and processing of large volumes of data, enabling data scientists and analysts to access and analyze data effectively.

Big Data Architect: Big data architects design and oversee the implementation of large-scale data systems and architectures. They specialize in managing distributed computing systems, data storage solutions, and data integration frameworks to support the processing of big data.

AI Ethicist: AI ethicists focus on the ethical implications of artificial intelligence (AI) and machine learning applications. They work with organizations to ensure responsible AI development, addressing concerns related to bias, fairness, transparency, and ethical use of data.

Quantitative Analyst (Quant): Quants apply mathematical and statistical models to financial data to develop trading strategies, risk management models, and investment recommendations. They work in financial institutions, hedge funds, and asset management firms, leveraging data analysis to drive investment decisions.

Research Scientist: Research scientists conduct research in academic or industrial settings to advance knowledge in data science, machine learning, and artificial intelligence. They publish findings in academic journals, collaborate on research projects, and contribute to innovations in data-driven technologies.

Consultant or Freelancer: Some graduates choose to work as data science consultants or freelancers, providing specialized expertise to organizations on a project basis. They offer services such as data analysis, predictive modeling, data visualization, and strategic advice on data-driven initiatives.