Computer science | Mei Yu | 2 | 40 |
Course Name: Data Mining | Course Code:S2293208 | |||||||||||||
Semester: 4 | Credit: 2 | |||||||||||||
Program: Computer science | ||||||||||||||
Course Module: Optional | ||||||||||||||
Responsible: Mei Yu | E-mail: wjr@tju.edu.cn | |||||||||||||
Department: Tianjin International Engineering Institute | ||||||||||||||
Time Allocation (1 credit hour = 45 minutes)
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Course Description The course is optional designed for Engineering Master of Computer Science in TIEI, and a course based on artificial intelligence, machine learning, pattern recognition, statistics and database, and could analyze data automatically, then give inductive reasoning. Adopting simple expressions, this course comprehensively and systematically introduces the basic concepts, methods, and technologies, as well as the latest progress of the database from the perspective of database and data warehouse. This course states top-ten algorithms in data mining in detail by application examples, in order to ensure that students could reach the effect of learning for practice. | ||||||||||||||
Prerequisite
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Course Objectives This course discusses basic concepts of data mining to help students find potential knowledge. After this course, students should be able to:
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Course Syllabus
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Textbooks & References
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Grade Distribution Survey: 12%; Experiments: 18%; Final Exam: 70% | ||||||||||||||
Capability Tasks CT2: To understand the basic concepts and steps of data mining. CT3: To master related algorithms, such as OLAP, classification, clustering, and prediction. CT4: To implement data mining’s algorithms under the particular environment. CS1: To master the basic theories of data mining, and understand the development status and trends of data mining. CS2: To grasp the top-ten processing algorithms of data mining to develop a system. | ||||||||||||||
Achievements
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Students: Computer science, Year2 |