B.S. in Data Science

Entry Requirements for Undergraduate programs

Application Fees : US$ 85

1. Academic Qualifications: Prospective undergraduate students are required to have a minimum academic achievement of 75% or above in their previous educational qualifications.

2. English Language Proficiency:  

   • IELTS Overall: A minimum overall band score of 6.5 on the IELTS.
   • TOEFL iBT Overall: A minimum overall score of 79 on the TOEFL iBT.
   • PTE Overall: A minimum overall score of 53 on the PTE Academic.
   • DET Score: A minimum score of 100 on the Duolingo English Test.

Score reporting is required.

The University of North Texas (UNT) offers a variety of scholarships to support international students in pursuing their education in the United States. These scholarships are designed to recognize academic achievement, leadership potential, and contributions to the UNT community. 

1. International Excellence Scholarship: This merit-based scholarship is awarded to new undergraduate and graduate international students. The scholarship amount varies and can significantly offset tuition costs.

2. International Education Scholarship: This scholarship is available for undergraduate and graduate students. It is awarded based on academic achievement, financial need, and contributions to international education on campus.

3. International Transfer Scholarship: International transfer students can apply for this scholarship, which is based on their academic performance at their previous institution. It helps ease the financial burden of transferring to UNT.

4. International Student Emergency Fund: UNT provides this fund to assist international students facing unexpected financial emergencies or hardships.

5. Cultural Scholarships: UNT offers cultural scholarships that recognize and celebrate students' cultural and ethnic backgrounds. These scholarships support diversity and promote cultural awareness on campus.

6. Graduate Assistantships: Many graduate programs at UNT offer assistantship opportunities that include a stipend and tuition benefits. These positions allow international graduate students to gain valuable research or teaching experience while pursuing their degrees.

7. Departmental Scholarships: Some academic departments and colleges within UNT may offer scholarships specific to students in their programs. These scholarships often consider academic achievement and area of study.

8. Athletic Scholarships: UNT offers athletic scholarships to student-athletes who excel in various sports. These scholarships are based on athletic performance and can cover tuition and related expenses.

9. External Scholarships: International students can explore external scholarship opportunities from organizations, governments, and foundations outside of UNT. The International Student Office can provide guidance on finding these scholarships.

10. Private Scholarships: Some private organizations and donors provide scholarships to international students. These scholarships may have specific eligibility criteria and application processes.

It's important to note that scholarship availability and eligibility criteria can change from year to year.

The Bachelor of Science (B.S.) in Data Science program at the University of North Texas (UNT) equips students with the skills and knowledge needed to excel in the dynamic field of data science. As organizations across various industries increasingly rely on data-driven decision-making, the demand for professionals with expertise in data science continues to grow. Graduates of UNT's B.S. in Data Science program are well-positioned to pursue diverse and rewarding career opportunities in the rapidly evolving field of data science. With their strong analytical skills, technical expertise, and domain knowledge, they can make significant contributions to organizations seeking to leverage data for strategic advantage and innovation.

1. Data Analyst: Graduates of the B.S. in Data Science program can pursue roles as data analysts, responsible for collecting, analyzing, and interpreting large datasets to identify trends, patterns, and insights. Data analysts play a crucial role in helping organizations make data-driven decisions, optimize processes, and improve performance across different business functions.

2. Data Scientist: Data scientists are analytical experts who leverage advanced statistical and machine learning techniques to extract actionable insights from complex datasets. They develop predictive models, algorithms, and data-driven solutions to solve business problems, optimize processes, and drive innovation. Data scientists work across various industries, including technology, finance, healthcare, and e-commerce.

3. Business Intelligence Analyst: Business intelligence analysts transform raw data into actionable insights to support strategic decision-making and business operations. They design and develop dashboards, reports, and data visualizations to communicate key performance indicators and trends to stakeholders. Business intelligence analysts play a critical role in helping organizations gain a competitive edge by harnessing the power of data analytics.

4. Machine Learning Engineer: Machine learning engineers design, build, and deploy machine learning models and algorithms to automate tasks, improve processes, and optimize performance. They work on projects such as natural language processing, computer vision, recommendation systems, and predictive analytics. Machine learning engineers collaborate with data scientists and software engineers to develop scalable and efficient machine learning solutions.

5. Data Engineer: Data engineers are responsible for designing, building, and maintaining data pipelines and infrastructure to support data-driven applications and analytics. They develop and deploy data processing systems, databases, and data warehouses to ingest, store, and analyze large volumes of data. Data engineers play a vital role in ensuring data quality, reliability, and accessibility for downstream analytics and decision-making.

6. Big Data Architect: Big data architects design and implement scalable and distributed systems to manage and process large volumes of data efficiently. They evaluate and select big data technologies and platforms, design data architectures, and oversee the implementation of big data solutions. Big data architects help organizations harness the power of big data to drive innovation, gain insights, and achieve business objectives.