B.A. in Accounting
The University of Utah offers a Bachelor of Arts (B.A.) in Accounting program designed ...
B.S. in Data Science
Salt Lake City, Utah
INTAKE: Jan & Aug
Program Overview
The Bachelor of Science (B.S.) in Data Science program at the University of Utah provides students with comprehensive training in data analysis, statistical modeling, programming, and machine learning techniques. The B.S. in Data Science program at the University of Utah equips students with a solid foundation in data analysis, statistical modeling, machine learning, and big data technologies, preparing them for diverse career opportunities in data-driven industries such as technology, healthcare, finance, e-commerce, and consulting. Graduates are well-positioned to pursue roles as data analysts, data scientists, machine learning engineers, business intelligence analysts, or research scientists in both private and public sectors.
Core Curriculum: The B.S. in Data Science program includes a core curriculum that covers foundational topics in mathematics, statistics, computer science, and data analysis. Students learn about probability theory, linear algebra, calculus, and discrete mathematics to develop a strong mathematical background essential for data analysis. Additionally, coursework in computer science introduces students to programming languages such as Python, R, SQL, and Java, enabling them to manipulate large datasets, develop algorithms, and build predictive models.
Data Visualization: Data visualization is a crucial aspect of data science, allowing professionals to communicate insights effectively and uncover patterns in complex datasets. Students in the program learn principles of data visualization and explore techniques for creating interactive visualizations, dashboards, and infographics using tools like Tableau, matplotlib, and ggplot2. Through hands-on projects and assignments, students gain proficiency in designing compelling visual representations of data to facilitate decision-making and storytelling.
Machine Learning and Predictive Modeling: The B.S. in Data Science program emphasizes machine learning algorithms and predictive modeling techniques used to extract valuable insights from data and make informed predictions. Students study supervised and unsupervised learning methods, including regression analysis, classification algorithms, clustering techniques, and dimensionality reduction. They learn how to apply machine learning algorithms to various domains, such as healthcare, finance, marketing, and natural language processing, to solve real-world problems and optimize business processes.
Big Data Analytics: With the exponential growth of data generated from diverse sources, proficiency in big data technologies and analytics is essential for data scientists. The program introduces students to distributed computing frameworks like Apache Hadoop, Spark, and MapReduce, enabling them to process and analyze large-scale datasets efficiently. Students also learn about data storage solutions, data preprocessing techniques, and cloud computing platforms for scalable and parallel processing of data.
Capstone Projects and Internships: As part of the B.S. in Data Science program, students engage in capstone projects and internships that provide hands-on experience in applying data science techniques to real-world problems. Working closely with industry partners, research labs, or faculty mentors, students tackle data-driven projects, analyze datasets, develop models, and present their findings to stakeholders. These practical experiences help students build a portfolio of projects, develop problem-solving skills, and gain industry exposure, enhancing their employability upon graduation.
Location
Salt Lake City, Utah
Score
IELTS: 6.5
Tuition Fee
USD 32378
Undergraduate Entry Requirements
Academic Requirements: Prospective undergraduate students are required to have a minimum academic achievement of 80% or above in their previous educational qualifications.
English language proficiency:
- IELTS Requirement: An overall IELTS score of 6.5 is required.
- TOEFL Requirement: A minimum overall score of 80 is often required.
- DET Requirement: A DET score of 105 is required.
Students must provide:
- academic marksheets & transcripts
- letters of recommendation
- a personal statement - SOP
- passport
- other supporting documents as required by the university.
It is important to note that meeting the minimum entry requirements does not guarantee admission, as the university considers factors such as availability of places and competition for the program. Additionally, some courses may have higher entry requirements or additional selection criteria, such as interviews or portfolio submissions.
The University of Utah offers various scholarships to support the academic endeavors of international students. These scholarships aim to recognize academic excellence, leadership potential, and diverse backgrounds, making education more accessible and affordable for students from around the world.
International Student Scholarships: The University of Utah provides merit-based scholarships specifically for international students. These scholarships may cover partial or full tuition costs and are awarded based on academic achievements, extracurricular involvement, and other criteria. International students are encouraged to check the university's scholarship website for eligibility requirements and application deadlines.
Departmental Scholarships: Many academic departments at the University of Utah offer scholarships to international students enrolled in their programs. These scholarships may be based on academic merit, financial need, or specific criteria related to the student's field of study. International students should inquire with their respective departments or academic advisors about available scholarship opportunities.
Diversity Scholarships: The University of Utah values diversity and strives to create an inclusive campus community. The university offers diversity scholarships to support students from underrepresented backgrounds, including international students. These scholarships aim to foster a diverse and vibrant learning environment where all students can thrive academically and personally.
International Student Exchange Programs: The University of Utah participates in various international student exchange programs that provide opportunities for incoming and outgoing exchange students to receive financial support. These programs may include scholarships, grants, or stipends to help cover tuition, travel expenses, and living costs during the exchange period. International students interested in studying abroad should explore exchange program opportunities through their home institutions or the University of Utah's international office.
External Scholarships and Funding Opportunities: In addition to university-sponsored scholarships, international students at the University of Utah can explore external scholarship opportunities offered by governments, organizations, foundations, and corporations. Many countries and institutions offer scholarships for international students to study abroad, and students are encouraged to research and apply for these external funding sources to supplement their financial aid packages.
The Bachelor of Science (B.S.) in Data Science program at the University of Utah offers graduates numerous career prospects in the rapidly growing field of data analytics and technology. The B.S. in Data Science program at the University of Utah prepares graduates for diverse and rewarding careers in data analytics, technology, finance, healthcare, and research, with ample opportunities for professional growth, advancement, and impact in the rapidly evolving field of data science.
Data Analyst: Graduates with a B.S. in Data Science can pursue careers as data analysts, where they are responsible for collecting, processing, and analyzing data to derive actionable insights. They work closely with stakeholders to identify trends, patterns, and correlations in data, helping organizations make informed decisions and optimize their operations.
Data Scientist: Data scientists play a crucial role in developing predictive models, machine learning algorithms, and statistical techniques to extract insights from data. With expertise in programming, statistics, and data visualization, graduates can work in various industries, including healthcare, finance, marketing, and technology, to solve complex problems and drive innovation.
Machine Learning Engineer: Machine learning engineers focus on designing, implementing, and deploying machine learning algorithms and models to automate tasks, improve processes, and enhance product functionalities. They collaborate with cross-functional teams to develop scalable and efficient solutions for tasks such as image recognition, natural language processing, and recommendation systems.
Business Intelligence Analyst: Business intelligence analysts leverage data to generate reports, dashboards, and visualizations that provide actionable insights to business stakeholders. They analyze market trends, customer behavior, and operational metrics to identify opportunities for growth, optimize performance, and drive strategic decision-making within organizations.
Data Engineer: Data engineers are responsible for designing, building, and maintaining data infrastructure and systems that enable the collection, storage, and processing of large volumes of data. They work with databases, data warehouses, and cloud platforms to ensure data quality, reliability, and accessibility for analytics and decision-making purposes.
Quantitative Analyst: Quantitative analysts, also known as quants, apply mathematical and statistical techniques to analyze financial markets, assess risk, and develop trading strategies for investment firms, hedge funds, and financial institutions. They utilize data science tools and algorithms to model market behavior, forecast trends, and optimize investment portfolios.
Research Scientist: Graduates interested in pursuing careers in academia or research institutions can work as research scientists, conducting studies, experiments, and data analyses to advance scientific knowledge and contribute to academic research in fields such as healthcare, environmental science, social sciences, and engineering.
Consultant: Data science graduates can also work as consultants, providing strategic advice, analytical solutions, and data-driven insights to clients across various industries. They may work for consulting firms, technology companies, or as independent contractors, helping organizations address business challenges, improve performance, and achieve their objectives through data-driven strategies.
