Data Science and Big Data Technology
1. Major introduction
Jointly launched by Tianjin University of Technology (TUT) and Bournemouth University (UK), this program adopts a "4+0" joint cultivation model and is affiliated to Bournemouth College of Tianjin University of Technology (to be established). By fully integrating the high-quality educational resources of both Chinese and British institutions, the program implements bilingual teaching, allowing students to study at Tianjin University of Technology for the entire duration. Students who complete the curriculum systems of both parties and meet the graduation requirements will be awarded a Bachelor of Engineering degree from Tianjin University of Technology and a Bachelor of Science degree from Bournemouth University (UK) respectively.
With "data-driven intelligent decision-making" as its core, the program builds its curriculum system around three dimensions: data management, system development, and intelligent analysis. It strengthens students' systematic capabilities in all links of data acquisition, processing, analysis, and visualization, and realizes the full-chain training from data theory to industrial application.
The training program is aligned with the professional certification standards of the British Computer Society (BCS). The curriculum system fully covers the key areas required by BCS, including computer science fundamentals, software engineering methods, system modeling and development, information security and ethics, as well as sustainability (LESP: Legal, Ethical, Social, and Professional issues). Emphasis is placed on cultivating students' comprehensive abilities in complex problem-solving, system design, and collaborative innovation, while also focusing on enhancing their engineering professional literacy and teamwork skills, providing a solid guarantee for students' future development in the international data and IT industry.
Relying on Tianjin University of Technology's disciplinary foundation in the fields of big data and artificial intelligence, and integrating Bournemouth University's teaching advantages in deep learning, business intelligence, data analysis, and decision support, the program builds an international cultivation platform featuring interdisciplinary integration and complementarity between Chinese and foreign strengths. Dedicated to nurturing high-level talents in data analysis and intelligent decision-making with a solid foundation in data science, good engineering literacy, and an international perspective, the program serves the regional economic development and the strategic needs of global digital transformation.
2. Cultivation objectives and degree requirements
2.1 Cultivation objectives
Facing the era of big data and the development needs of emerging fields such as artificial intelligence, blockchain, intelligent transportation, and bioinformatics, this major aims to cultivate international innovative talents who meet the requirements of economic construction and social development. These talents will master the core knowledge and skills in the field of data science and big data technology, possess sound comprehensive literacy, professional theoretical foundation and international perspective, and achieve all-round development in moral, intellectual, physical, aesthetic and labor education. Graduates will be competent in work such as big data analysis, processing, mining, visualization and big data application software development, and have lifelong learning ability, teamwork ability and innovation ability.
After approximately 5 years of engineering practice and learning, graduates are expected to meet the following requirements:
1) Possess patriotism, social responsibility and sound comprehensive literacy, abide by the professional ethics of engineers, serve the development of the industry and social progress with an international perspective, and contribute to Sino-foreign technological exchanges and industrial cooperation.
2) Have the ability to perceive international cutting-edge technologies and engineering innovation capabilities, be able to analyze practical application problems in the field of big data and emerging areas and propose solutions, and play a key role in the application of core big data technologies and practice in emerging interdisciplinary fields.
3) Possess cross-cultural teamwork, organization, coordination and communication skills, be able to integrate professional advantages in multi-disciplinary international projects, grow into the backbone of project teams, and promote the implementation of transnational technological cooperation.
4) Have industry adaptability and technological foresight, be able to keep up with the pace of international big data technology transformation and the development trend of emerging fields through continuous learning, and achieve dynamic improvement of professional capabilities.
2.2 Degree requirements
According to the talent cultivation goals outlined in the professional training program, the major proposes 11 graduation requirements. The specific content is as follows:
A. Be able to apply knowledge of mathematics, natural sciences, engineering fundamentals, and professional expertise to solve complex engineering problems in the field of data science and big data technology.
B. Possess computational thinking and systematic thinking, and be able to apply the basic principles of mathematics, natural sciences, and engineering sciences to identify, express, and analyze complex engineering problems in the field of big data technology applications through literature research, and obtain effective conclusions with comprehensive consideration of the requirements of sustainable development.
C. Be able to design solutions for complex engineering problems related to big data technology. The design schemes shall comply with software engineering specifications, and reflect a sense of innovation in the design process. Meanwhile, factors such as society, health, safety, law, culture and environment shall be taken into account.
D. Be able to research complex engineering problems in the field of big data technology applications based on scientific principles including those from computational disciplines, using scientific methods. This includes designing experiments, analyzing and interpreting data, and drawing reasonable and valid conclusions through information synthesis.
E. Be able to develop, select, and use appropriate technologies, resources, modern engineering tools, and information technology tools for complex engineering problems in big data technology—including predicting and simulating complex engineering problems—and understand their limitations.
F. Understand the country’s relevant policies on the development of the information industry; be able to analyze and evaluate the impact of complex engineering practices and solutions in data science and big data technology on health, safety, the environment, law, as well as economic and social sustainable development based on relevant background knowledge; and understand the responsibilities to be undertaken.
G. Possess a sense of family and country as well as social responsibility; be able to understand and apply engineering ethics, abide by professional ethics and norms, and fulfill social responsibilities in big data technology engineering practices.
H. Have a strong physique and good overall quality; be able to adapt to teamwork in a multidisciplinary context and take on roles as an individual, team member, or leader within a team.
I. Be able to effectively communicate and exchange ideas with industry peers and the public on complex engineering problems in the field of big data technology applications—including writing reports and design documents, making presentations, clearly expressing or responding to instructions; be able to understand cultural differences and communicate in a cross-cultural context.
J. Possess a certain level of project management ability in big data technology; understand and master management principles and economic decision-making methods related to engineering projects, and be able to apply them across industries.
K. Have critical thinking, be able to understand the impact of industry development and technological changes, and have the ability to continuously learn and adapt to the rapid development of big data technology.
