Bachelor of Science in Data Science
September 29, 2026 2026-09-29 3:37Bachelor of Science in Data Science
A program that prepares students to collect, manage, analyze, visualize, and interpret data to support evidence-based decision-making across a wide range of industries. The program integrates computer science, mathematics, statistics, machine learning, data engineering, artificial intelligence, business analytics, and data visualization to develop professionals capable of transforming complex data into meaningful insights.
Bachelor of Science (B.S.) in Data Science
US$ 7,360
3–4 Years — Traditional Learning Track
9–12 Months — Fast-Track Learning Program
3–4 Years
9–12 Months
3 Credit Hours
US$ 7,360
Transform Complex Data into Meaningful Insights
An interdisciplinary program integrating computer science, mathematics, statistics, machine learning, data engineering, artificial intelligence, business analytics, and data visualization.
The Bachelor of Science in Data Science prepares students to collect, manage, analyze, visualize, and interpret data to support evidence-based decision-making across a wide range of industries. The program integrates computer science, mathematics, statistics, machine learning, data engineering, artificial intelligence, business analytics, and data visualization to develop professionals capable of transforming complex data into meaningful insights.
Students develop expertise in programming, mathematical foundations, probability and statistics, data structures, database systems, data engineering, visualization, machine learning, predictive analytics, big data, artificial intelligence, cloud computing, data mining, business intelligence, ethics and governance, research methods, and professional communication. The curriculum emphasizes hands-on analytical work, evidence-based problem-solving, and the practical application of data science across industries.
The program prepares graduates for careers in technology, healthcare, finance, business, government, research, manufacturing, telecommunications, education, and consulting. It also provides an excellent academic foundation for graduate study in data science, artificial intelligence, computer science, business analytics, statistics, machine learning, information systems, and related disciplines.
Bachelor of Science (B.S.) in Data Science
3–4 Years — Traditional Learning Track
9–12 Months — Fast-Track Learning Program
3 Credit Hours per Course
US$ 7,360
Exclusive of applicable University administrative fees
Required Major Courses
The major consists of coursework in programming, mathematics, probability and statistics, data structures, database systems, data engineering, visualization, machine learning, predictive analytics, big data, artificial intelligence, cloud computing, data mining, business intelligence, ethics and governance, research methods, and professional communication. Students also complete the University's General Education requirements together with approved elective coursework.
| Course No. | Course Title | Credits |
|---|---|---|
| DS 3000 | Introduction to Data Science | 3 |
| DS 3010 | Programming for Data Science | 3 |
| DS 3020 | Calculus and Linear Algebra for Data Science | 3 |
| DS 3030 | Probability and Statistics | 3 |
| DS 3040 | Data Structures and Algorithms | 3 |
| DS 3050 | Database Management Systems | 3 |
| DS 3060 | Data Engineering | 3 |
| DS 3070 | Data Visualization | 3 |
| DS 3080 | Machine Learning Fundamentals | 3 |
| DS 3090 | Predictive Analytics | 3 |
| DS 3100 | Big Data Analytics | 3 |
| DS 3110 | Artificial Intelligence for Data Science | 3 |
| DS 3120 | Cloud Computing for Data Analytics | 3 |
| DS 3130 | Data Mining and Knowledge Discovery | 3 |
| DS 3140 | Business Intelligence and Decision Support | 3 |
| DS 3150 | Ethics, Privacy, and Data Governance | 3 |
| DS 3160 | Research Methods for Data Science | 3 |
| DS 3170 | Applied Data Science Across Industries | 3 |
| DS 3180 | Professional Communication for Data Scientists | 3 |
| DS 3190 | Capstone Project in Data Science | 6 |
| Total Credits | 63 | |
Course Descriptions
Select a course to view its description.
DS 3000 – Introduction to Data Science
Introduces the principles of data science, the data lifecycle, analytical thinking, data-driven decision-making, and contemporary applications across industries.
DS 3010 – Programming for Data Science
Develops programming skills for data analysis using modern programming languages, emphasizing data manipulation, automation, and computational problem-solving.
DS 3020 – Calculus and Linear Algebra for Data Science
Examines mathematical concepts including functions, matrices, vectors, optimization, and linear transformations used in data science and machine learning.
DS 3030 – Probability and Statistics
Introduces probability distributions, statistical inference, hypothesis testing, regression, sampling methods, and exploratory data analysis.
DS 3040 – Data Structures and Algorithms
Explores efficient data organization, algorithm design, computational complexity, searching, sorting, and optimization techniques.
DS 3050 – Database Management Systems
Examines relational databases, SQL, NoSQL systems, database design, normalization, and data management principles.
DS 3060 – Data Engineering
Focuses on data pipelines, extract-transform-load (ETL) processes, distributed data systems, data warehousing, and scalable data architectures.
DS 3070 – Data Visualization
Develops skills in designing effective visualizations, dashboards, storytelling with data, and communicating analytical insights.
DS 3080 – Machine Learning Fundamentals
Introduces supervised and unsupervised learning, predictive modeling, classification, clustering, model evaluation, and feature engineering.
DS 3090 – Predictive Analytics
Examines statistical forecasting, predictive modeling techniques, business forecasting, and decision-support systems.
DS 3100 – Big Data Analytics
Explores distributed computing, large-scale data processing, cloud analytics, and technologies for managing high-volume datasets.
DS 3110 – Artificial Intelligence for Data Science
Examines AI methods, intelligent systems, neural networks, and the integration of artificial intelligence into data analytics workflows.
DS 3120 – Cloud Computing for Data Analytics
Introduces cloud platforms, data storage, scalable analytics, cloud-native services, and deployment of data science applications.
DS 3130 – Data Mining and Knowledge Discovery
Studies pattern recognition, association analysis, anomaly detection, clustering, and extracting actionable knowledge from complex datasets.
DS 3140 – Business Intelligence and Decision Support
Focuses on business intelligence systems, key performance indicators, reporting, dashboards, and strategic decision-making.
DS 3150 – Ethics, Privacy, and Data Governance
Examines responsible data use, privacy protection, data governance, regulatory compliance, bias mitigation, and ethical decision-making.
DS 3160 – Research Methods for Data Science
Develops competencies in research design, experimental methods, data collection, reproducible research, and evidence-based analysis.
DS 3170 – Applied Data Science Across Industries
Explores practical applications of data science in healthcare, finance, marketing, manufacturing, cybersecurity, education, and public policy.
DS 3180 – Professional Communication for Data Scientists
Develops technical writing, presentation skills, stakeholder communication, project documentation, and collaborative problem-solving.
DS 3190 – Capstone Project in Data Science
Students integrate programming, statistical analysis, machine learning, data engineering, and visualization by designing and presenting a comprehensive data science project addressing a real-world challenge.
Career Opportunities
Graduates are prepared for careers in data science, data analysis, business intelligence, machine learning, data engineering, analytics consulting, and quantitative analysis.
Employment Sectors
Graduates may find employment in technology companies, financial institutions, healthcare organizations, government agencies, research institutions, manufacturing companies, retail and e-commerce organizations, telecommunications companies, consulting firms, insurance companies, logistics and supply chain organizations, and educational institutions.
Ready to Turn Data into Insights?
Gain the analytical, technical, and communication skills needed to transform complex data into meaningful insights. Take the next step toward a career in data science or graduate study.
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