Data Science University of California, Riverside

Overview

The Data Science programme at the University of California, Riverside provides students with the technical expertise required to decode complex datasets. This comprehensive curriculum focuses on identifying hidden patterns and extracting critical information to drive strategic decision-making in various global industries.

Students engage with a rigorous academic framework that combines leadership strategy with advanced technical skills. The course is delivered entirely online, ensuring that working professionals can advance their education without relocating or interrupting their current career trajectories.

The teaching methodology emphasises practical application, allowing learners to develop efficient techniques for data mining and statistical analysis.

Why Data Science at the University of California, Riverside?

The university holds a distinguished reputation, with its online information technology offerings ranked 17th by U.S. News & World Report. It is regionally accredited by the Western Association of Schools and Colleges, ensuring the highest educational standards and a commitment to continuous improvement.

The institution is also recognised as a national leader for social mobility, reflecting a diverse and inclusive learning environment. Students benefit from an entrepreneurial faculty that fosters innovation and collaboration, making a significant global impact through research and teaching excellence.

The programme structure is uniquely accommodating, featuring three start dates per year and no residency requirements. Instead of a traditional thesis, students complete four one-credit capstone courses that provide a rich, flexible learning experience tailored to professional needs.

Tuition Fee Breakdown

• International fee: USD 36396 per full
• National fee: USD 36396 per full
• Local fee: USD 36396 per full

Visit the Fees and Funding section for a breakdown in your local currency.

Syllabus

The curriculum consists of 16 credits of core engineering classes and 16 credits of specialised data topics. Modules may include:

Core Engineering Modules

• Engineering in the Global Environment
• Technology Innovation and Strategy for Engineers
• Systems Engineering
• Engineering Management

Specialisation Modules

• Applied Machine Learning
• Visualization in Data Science
• Data Mining Techniques
• Computer Vision
• Statistical Computing
• Statistical Mining Methods
• Machine Learning
• Information Retrieval & Web Search
• Data Visualization & Big Data Tools

Careers with Data Science

Graduates are prepared for high-level roles across the medical, financial, retail, and telecommunications sectors. The demand for data professionals continues to grow as organisations seek experts to manage and interpret vast quantities of information for competitive advantage.

Potential career paths include becoming a Chief Data Officer, responsible for shaping organisational data policies and supervising technical staff. Other opportunities exist as E-commerce Data Specialists, who analyse consumer habits to improve retail experiences and predictive offerings.

Graduates may also pursue roles as Social Media Data Analysts, scrutinising global networking trends to help brands create targeted advertising. The skills acquired during the programme are applicable to major global employers such as Amazon, IBM, and American Express.