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Data Science and Big Data Technology

From healthcare and finance to transportation, education, and entertainment, the digital transformation of our world generates an unprecedented volume, variety, and velocity of data. The true potential of this raw big data lies in our ability to extract meaningful insights, predict future trends, and support informed decision-making. The Data Science (DS) program at Global College is an interdisciplinary program that sits at the intersection of statistics, computer science, and application-specific knowledge. It is designed to equip students with the theoretical foundations and practical data analytical and programming skills necessary to turn raw data into actionable intelligence.

The DS program provides students with a fundamental background in the core theoretical concepts and practical techniques of modern data science and engineering. It is built on a common science and engineering core. All students first receive rigorous instruction in mathematics, statistics, physics, engineering basics, artificial intelligence, and computer programming. Built on these foundations, an array of program subjects, technical cores, and upper-level technical electives enables students to tailor their data science and engineering education to best suit their career goals. A flexible curriculum allows students to emphasize a wide variety of subject areas within the field, including statistical learning,  database management, artificial intelligence, data mining, data privacy and security, cloud computing, and data-driven applications across diverse domains.

A degree in data science can lead to a wide range of career opportunities. Data scientists develop predictive models, analytical frameworks, optimization methods, and decision-support systems for complex data-driven problems across a wide range of domains. Data scientists develop models and analytical tools for intelligent systems, quality control, predictive maintenance, process optimization, and other data-driven engineering applications. In scientific settings, they work with complex experimental, observational, and simulation data to support discovery, modeling, and quantitative analysis in areas such as healthcare, biology, physics, and other research domains. Data scientists contribute to business intelligence, customer and market analytics, sales forecasting, fraud detection, and decision-support systems. Across these contexts, data scientists design, build, test, and deploy machine learning models, data pipelines, and user-facing data applications that support prediction, automation, and informed decision-making.

Program Educational Objectives

Within 3 to 5 years after graduation from the DS program, the graduates are expected to:

  • Further their intellectual growth through graduate education or professional development.
  • Apply their creativity and global perspective in their engineering or non-engineering professions.
  • Assume leadership roles in a variety of contexts.
Student Outcomes

Graduates from the DS program should be able to demonstrate:

  1. an ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics
  2. an ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors
  3. an ability to communicate effectively with a range of audiences
  4. an ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts
  5. an ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives
  6. an ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions
  7. an ability to acquire and apply new knowledge as needed, using appropriate learning strategies
Curriculum

Candidates for the Bachelor of Science in DS must satisfactorily complete 122 credit hours required by the GC DS program, including:

  • Engineering Foundation 38 credits 
  • Program Subjects 35 credits
  • Engineering Specialization 4 credits
  • Academic Writing 4 credits
  • Intellectual Breadth 14 credits
  • Electives 27 credits:
  • DS Applications Electives 8 credits
  • Flexible Technical Electives 8 credits
  • General Electives 11 credits

Additionally, domestic Chinese students are also required to take all courses required by the Ministry of Education of China. International students are required to take 12 credits of Chinese language and culture courses.