I. Training Objectives

The Computer Science Department strives for excellence in imparting and applying knowledge in Data Science and Big Data Technology through comprehensive educational programs, practical training and research in collaboration with industry and government. Our main educational objective is to make in-depth and valuable contributions to apply data mining and big data analysis technology of computer science on finance, engineering and other application areas, to demonstrate strong self-learning and self-directed problem solving abilities, communication skills and the ability to function effectively as part of a team, to demonstrate a sense of societal and ethical responsibility in all professional endeavors. Data mining, also called knowledge discovery in databases, in computer science, the process of discovering interesting and useful patterns and relationships in large volumes of data. The field combines tools from statistics and artificial intelligence (such as neural networks and machine learning) with database management to analyze large digital collections, known as data sets. Data mining is widely used in business (insurance, banking, retail), science research (astronomy, medicine), and government security (detection of criminals and terrorists). II. Core Courses Discrete Mathematics, Principle of Circuits, Programming Fundamentals, Object-Oriented Programming, Computer Principles, Data Structure, Algorithm Analysis and Design, Database principles, Artificial Intelligence, Machine Learning, Mobile Application Development, Data Mining, C++ Programing, Big Data Analysis, Application and Development of Big Data Technology, Mathematical Software. III. Main Internship and Practice
Including apprenticeship, project practice, internship and thesis. V. Length of Schooling, Degree and Credits Requirements for Graduation

1．Length of Schooling：The length of schooling is four years and no longer than six years.

2．Degree Conferred: Bachelor of Engineering degree in Computer Science

3．The Graduation Credits：143

4．Pass HSK 4 (new format) (score 180)

VI．The curriculum and distribution of credits

1. Curriculum: Teaching is divided into theoretical and practical teaching. Among them, the theoretical teaching is compulsory, and students may choose some
elective courses from other departments, which is not compulsory.

2. A list of the credit allocation

Table 1： List of the Credit Allocation

3. The curriculum and course arrangement

Table2: Curriculum and Course Arrangement

Note: Students who have passed HSK3(new format) will be exempt from Elementary Chinese, Elementary Chinese Listening and Speaking; Students who have passed HSK4(new format) will be exempt from Elementary Chinese, Elementary Chinese Listening and Speaking, Intermediate Chinese, Intermediate Chinese Listening and Speaking. Those students can get the credits of corresponding courses after confirmation.