NCKU Curriculum Map
1. 2.
3.
BIG DATA ANALYTICS AND DATA MINING

Due to the different types of big data in various fields, how to extract such big data through a series of processes to produce potentially useful information becomes an essential issue in various fields. This course will firstly teach the basic concepts and pre-processing methods of dealing with big data, and then teach a series of theories and methods of big data analytics and data mining, including: association rules, rough set theory, decision tree analysis, principal component analysis, cluster analysis, regression analysis, Bayesian classification and neural networks. Through the Python programming language of current mainstream big data analytics tools, students are trained to use the concepts of machine learning, data mining and statistics to design different big data analytics models. It is hoped that students can have the basic ability to analyze big data through this course.

Course Goal
A. Develop knowledge and experience in the application of resources engineering principles for the exploitation of earth's resources
B. Develop knowledge and experience ensure prudent and provident use of resources in a sustainable global society.
Course Principle Literacy and Competence
[Competence]
  • Ability of computer application
  • NO
  • Ability of using the basic science (mathematics, science, engineering) knowledge
  • NO
  • Ability of planning and execution for theses
  • NO
    Courses of Recent Years
    Year/
    Semester
    Course
    Number
    Class
    Code
    Course Name
    (The name will link to the syllabus.)
    Credit Taught in English
    (Yes or No)
    Instructor
    0108/2 E435200 [RE3302]BIG DATA ANALYTICS AND DATA MINING 3.0 N